Atrial arrhythmia episode detection in a cardiac medical device

ABSTRACT

A medical device is configured to detect an atrial tachyarrhythmia episode. The device senses a cardiac signal, identifies R-waves in the cardiac signal attendant ventricular depolarizations and determines classification factors from the R-waves identified over a predetermined time period. The device classifies the predetermined time period as one of unclassified, atrial tachyarrhythmia and non-atrial tachyarrhythmia by comparing the determined classification factors to classification criteria. A classification criterion is adjusted from a first classification criterion to a second classification criterion after at least one time period being classified as atrial tachyarrhythmia. An atrial tachyarrhythmia episode is detected by the device in response to at least one subsequent time period being classified as atrial tachyarrhythmia based on the adjusted classification criterion.

REFERENCE TO RELATED APPLICATION

This application is a continuation application of pending U.S. patentapplication Ser. No. 16/051,779, filed on Aug. 1, 2018 (published asU.S. Pub. No. 2018/0338699), which is a continuation application of U.S.patent application Ser. No. 15/084,511, filed on Mar. 30, 2016 (grantedas U.S. Pat. No. 10,045,710), the content of both of which isincorporated herein by reference in their entirety.

TECHNICAL FIELD

The disclosure relates generally to cardiac medical devices and, inparticular, to a cardiac medical device and method for detecting atrialarrhythmia episodes from sensed cardiac electrical signals.

BACKGROUND

During normal sinus rhythm (NSR), the heart beat is regulated byelectrical signals produced by the sino-atrial (SA) node located in theright atrial wall. Each atrial depolarization signal produced by the SAnode spreads across the atria, causing the depolarization andcontraction of the atria, and arrives at the atrioventricular (A-V)node. The A-V node responds by propagating a ventricular depolarizationsignal through the bundle of His of the ventricular septum andthereafter to the bundle branches and the Purkinje muscle fibers of theright and left ventricles.

Atrial tachyarrhythmia includes the disorganized form of atrialfibrillation and varying degrees of organized atrial tachycardia,including atrial flutter. Atrial fibrillation (AF) occurs because ofmultiple focal triggers in the atrium or because of changes in thesubstrate of the atrium causing heterogeneities in conduction throughdifferent regions of the atria. The ectopic triggers can originateanywhere in the left or right atrium or pulmonary veins. The AV nodewill be bombarded by frequent and irregular atrial activations but willonly conduct a depolarization signal when the AV node is not refractory.The ventricular cycle lengths will be irregular and will depend on thedifferent states of refractoriness of the AV-node.

As more serious consequences of persistent atrial arrhythmias have cometo be understood, such as an associated risk of relatively more seriousventricular arrhythmias and stroke, there is a growing interest inmonitoring and treating atrial arrhythmias. Implantable cardiac monitorsand implantable cardioverter defibrillators (ICDs) may be configured toacquire cardiac electrical signals that can be analyzed for detectingatrial arrhythmias.

SUMMARY

In general, the disclosure is directed to techniques for detectingcardiac events, more specifically atrial tachyarrhythmia episodes, by amedical device. A medical device operating according to the techniquesdisclosed herein analyzes a cardiac electrical signal over a pluralityof time periods and classifies each of the time periods based oncharacteristics of the cardiac electrical signal, such ascharacteristics of the RR-intervals occurring during each of theplurality of time periods. The device may adjust a threshold forclassifying the cardiac signal for at least a portion of the timeperiods. An atrial tachyarrhythmia may be detected when a predeterminednumber of time periods are classified as atrial tachyarrhythmia, whichmay include at least one time period before the threshold adjustment andone or more time periods after the threshold adjustment.

In one example, the disclosure provides a method of detecting an atrialtachyarrhythmia episode in a medical device. The method comprisessensing a cardiac signal and identifying R-waves in the cardiac signalattendant ventricular depolarizations. The method also includesdetermining classification factors from the R-waves identified over afirst predetermined time period and classifying the first predeterminedtime period as atrial tachyarrhythmia based on comparing the determinedclassification factors to classification criteria. The method furtherincludes adjusting a classification criterion of the classificationcriteria from a first classification criterion to a secondclassification criterion after classifying the first time period asatrial tachyarrhythmia, classifying at least one subsequent time periodas atrial tachyarrhythmia by comparing classification factors determinedover the subsequent time period to the adjusted classificationcriterion; and detecting an atrial tachyarrhythmia episode in responseto at least one subsequent time period being classified as atrialtachyarrhythmia based on the adjusted classification criteria.

In another example, the disclosure provides a medical device fordetecting an atrial tachyarrhythmia episode. The medical device includessensing circuitry configured to receive a cardiac signal from aplurality of electrodes coupled to the medical device. The medicaldevice also includes a processor configured to identify R-waves in thecardiac signal attendant ventricular depolarizations, determineclassification factors from the R-waves identified over a firstpredetermined time period, and classify the first predetermined timeperiod as atrial tachyarrhythmia based on comparing the determinedclassification factors to classification criteria. The processor isfurther configured to adjust a classification criterion of theclassification criteria from a first classification criterion to asecond classification criterion after the first time period beingclassified as atrial tachyarrhythmia, classify at least one subsequenttime period as atrial tachyarrhythmia by comparing classificationfactors determined over the subsequent time period to the adjustedclassification criterion, and detect an atrial tachyarrhythmia episodein response to at least one subsequent time period being classified asatrial tachyarrhythmia based on the adjusted classification criterion.

In another example, the disclosure provides a non-transitory,computer-readable storage medium storing instructions for causing aprocessor included in a medical device to perform a method for detectingan atrial tachyarrhythmia episode. The method comprises sensing acardiac signal and identifying R-waves in the cardiac signal attendantventricular depolarizations. The method also includes determiningclassification factors from the R-waves identified over a firstpredetermined time period and classifying the first predetermined timeperiod as atrial tachyarrhythmia based on comparing the determinedclassification factors to classification criteria. The method furtherincludes adjusting a classification criterion of the classificationcriteria from a first classification criterion to a secondclassification criterion after classifying the first time period asatrial tachyarrhythmia, classifying at least one subsequent time periodas atrial tachyarrhythmia by comparing classification factors determinedover the subsequent time period to the adjusted classificationcriterion; and detecting an atrial tachyarrhythmia episode in responseto at least one subsequent time period being classified as atrialtachyarrhythmia based on the adjusted classification criteria.

This summary is intended to provide an overview of the subject matterdescribed in this disclosure. It is not intended to provide an exclusiveor exhaustive explanation of the apparatus and methods described indetail within the accompanying drawings and description below. Furtherdetails of one or more examples are set forth in the accompanyingdrawings and the description below.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a conceptual diagram of an implantable medical device (IMD)system for detecting atrial arrhythmias according to one example.

FIG. 1B is a conceptual diagram of an IMD system for detecting atrialtachyarrhythmia according to another example.

FIG. 1C is a conceptual diagram of yet another IMD system in whichtechniques disclosed herein may be implemented for detecting atrialtachyarrhythmia.

FIG. 2 is a functional schematic diagram of the implantable cardioverterdefibrillator (ICD) of FIG. 1 .

FIGS. 3A and 3B are conceptual diagrams of an alternative ICD systemthat may be configured to detect atrial tachyarrhythmia according to thetechniques disclosed herein.

FIG. 4 is a schematic diagram of methods used for detecting cardiacevents by any of the ICDs of FIGS. 1A, 1B and 2 or the monitoring deviceof FIG. 1C according to one example.

FIG. 5 is a diagram of a two-dimensional histogram representing a Lorenzplot area used in the techniques disclosed herein for detecting atrialtachyarrhythmia.

FIG. 6 is flowchart of a method for determining a factor for classifyingtime periods for detecting atrial tachyarrhythmia according to oneexample.

FIG. 7 is a flowchart of a method for classifying a predetermined timeperiod for use in detecting atrial tachyarrhythmia according to oneexample.

FIG. 8 is a schematic diagram of atrial fibrillation detection that maybe performed by the ICDs shown in FIGS. 1A, 1B and 3A or the monitor ofFIG. 1C.

FIG. 9 is a schematic diagram of a method for detecting atrialfibrillation by an ICD or implantable monitoring device according toanother example.

FIG. 10 is a flowchart of a method for detecting atrial fibrillation,according to one example.

FIG. 11 is a flow chart of a method performed by an ICD or implantablemonitor for providing a response to detecting atrial tachyarrhythmiaaccording to one example.

DETAILED DESCRIPTION

In the following description, references are made to illustrativeembodiments for carrying out the methods described herein. It isunderstood that other embodiments may be utilized without departing fromthe scope of the disclosure.

In various examples, a cardiac electrical signal is used for determiningsuccessive ventricular cycle lengths for use in detecting atrialarrhythmias. Ventricular cycle lengths may be determined as intervalsbetween successive R-waves that are sensed from the cardiac electricalsignal and attendant to the depolarization of the ventricles. Thedifferences between successive RR intervals (RRIs) are analyzed fordetermining evidence of atrial tachyarrhythmia, e.g., atrialfibrillation. As described herein, a time period of the cardiac signalmay be classified as AF, non-AF, or unclassified based on an analysis ofthe RRIs and other factors. When a predetermined number of time periodsof the cardiac signal are classified as AF, a medical device operatingaccording to the techniques disclosed herein may detect AF. The device,however, may adjust a classification criterion applied for classifying atime period of the cardiac signal prior to detecting AF and detect AFbased on the adjusted classification criterion applied for classifyingsubsequent time periods.

Aspects of the methods described herein can be incorporated in a varietyof implantable or external medical devices having cardiac signalmonitoring capabilities, which may or may not include therapy deliverycapabilities. Such devices include single chamber, dual chamber orbi-ventricular pacing systems or ICDs that sense the R-waves and deliveran electrical stimulation therapy to the ventricles. The atrialarrhythmia detection methods presently disclosed may also beincorporated in implantable cardiac monitors having implantableelectrodes or external cardiac monitors having electrocardiogram (ECG)electrodes coupled to the patient's skin to detect R-waves, e.g., Holtermonitors, or within computerized systems that analyze pre-recorded ECGor cardiac electrogram (EGM) data. Embodiments may further beimplemented in a patient monitoring system, such as a centralizedcomputer system which processes cardiac electrical signals and otherdata sent to it by implantable or wearable monitoring devices.

FIG. 1 is a conceptual diagram of an implantable medical device (IMD)system 1 for detecting atrial arrhythmias according to one example. TheIMD system 1 of FIG. 1 includes an implantable cardioverterdefibrillator (ICD) 10 coupled to a patient's heart 2 via transvenouselectrical leads 6, 11, and 16. ICD 10 includes a connector block 12that may be configured to receive the proximal ends of a rightventricular (RV) lead 16, a right atrial (RA) lead 11 and a coronarysinus (CS) lead 6, which are advanced transvenously for positioningelectrodes for sensing and stimulation in three or all four heartchambers.

RV lead 16 is positioned such that its distal end is in the rightventricle for sensing RV cardiac signals and delivering pacing orshocking pulses in the right ventricle. For these purposes, RV lead 16is equipped with pacing and sensing electrodes shown as a ring electrode30 and a tip electrode 28. In some examples, tip electrode 28 is anextendable helix electrode mounted retractably within an electrode head29. RV lead 16 is further shown to carry defibrillation electrodes 24and 26, which may be elongated coil electrodes used to deliver highvoltage cardioversion/defibrillation (CV/DF) electrodes. Defibrillationelectrode 24 is referred to herein as the “RV defibrillation electrode”or “RV coil electrode” because it may be carried along RV lead 16 suchthat it is positioned substantially within the right ventricle whendistal pacing and sensing electrodes 28 and 30 are positioned for pacingand sensing in the right ventricle. Defibrillation electrode 26 isreferred to herein as a “superior vena cava (SVC) defibrillationelectrode” or “SVC coil electrode” because it may be carried along RVlead 16 such that it is positioned at least partially along the SVC whenthe distal end of RV lead 16 is advanced within the right ventricle.

Each of electrodes 24, 26, 28 and 30 are connected to a respectiveinsulated conductor extending within the body of lead 16. The proximalend of the insulated conductors are coupled to corresponding connectorscarried by proximal lead connector 14, e.g., a DF-4 connector, at theproximal end of lead 16 for providing electrical connection to ICD 10.It is understood that although ICD 10 is illustrated in FIG. 1 as amulti-chamber chamber device coupled to RA lead 11 and CS lead 6, ICD 10may be configured as a single chamber device coupled only to RV lead 16as shown and described in conjunction with FIG. 1B below. The techniquesdisclosed herein for detecting atrial tachyarrhythmia may besuccessfully performed without requiring atrial signal sensing. As such,RA lead 11 is optional in some examples.

If included, RA lead 11 may be positioned such that its distal end is inthe vicinity of the right atrium and the superior vena cava. Lead 11 isequipped with pacing and sensing electrodes 17 and 21 shown as a tipelectrode 17, which may be an extendable helix electrode mountedretractably within electrode head 19, and a ring electrode 21 spacedproximally from tip electrode 17. The electrodes 17 and 21 providesensing and pacing in the right atrium and are each connected to arespective insulated conductor with the body of RA lead 11. Eachinsulated conductor is coupled at its proximal end to connector carriedby proximal lead connector 13.

CS lead 6 is also optional and not required to successfully execute theatrial tachyarrhythmia detection methods disclosed herein. When present,CS lead 6 may be advanced within the vasculature of the left side of theheart via the coronary sinus and a cardiac vein 18. CS lead 6 is shownin the embodiment of FIG. 1A as having one or more electrodes 8 that maybe used in combination with either RV coil electrode 24 or the SVC coilelectrode 26 for delivering electrical shocks for cardioversion anddefibrillation therapies. In other examples, coronary sinus lead 6 mayalso be equipped with one or more electrodes 8 for use in deliveringpacing and or sensing cardiac electrical signals in the left chambers ofthe heart, i.e., the left ventricle and/or the left atrium. The one ormore electrodes 8 are coupled to respective insulated conductors withinthe body of CS lead 6, which provides connection to the proximal leadconnector 4.

The RV pacing and sensing electrodes 28 and 30 may be used as a bipolarpair, commonly referred to as a “tip-to-ring” configuration for sensingcardiac electrical signals. Further, RV tip electrode 28 may be selectedwith a coil electrode 8, 24, or 26 to be used as an integrated bipolarpair, commonly referred to as a “tip-to-coil” configuration for sensingcardiac electrical signals. ICD 10 may, for example, select one or moresensing electrode vectors including a tip-to-ring sensing vector betweenelectrodes 28 and 30 and a tip-to-coil sensing vector, e.g., between RVtip electrode 28 and SVC coil electrode 26, between RV tip electrode 28and RV coil electrode 24, between RV ring electrode 30 and SVC coilelectrode 26 or between RV ring electrode 30 and RV coil electrode 24.In some cases, any of the electrodes 24, 26, 28 or 30 carried by RV lead16 may be selected by ICD 10 in a unipolar sensing configuration withthe ICD housing 15 serving as the indifferent electrode, commonlyreferred to as the “can” or “case” electrode. It is recognized thatnumerous sensing and electrical stimulation electrode vectors may beavailable using the various electrodes carried by one or more of leads6, 11 and 16 coupled to ICD 10, and ICD 10 may be configured toselectively couple one or more sensing electrode vector to sensingcircuitry enclosed by housing 15, e.g., sensing circuitry including oneor more amplifiers, filters, rectifiers, comparators, sense amplifiers,analog-to-digital convertors and/or other circuitry configured toacquire a cardiac electrical signal for use in detecting cardiacarrhythmias.

In other examples, the ICD housing 15 may serve as a subcutaneousdefibrillation electrode in combination with one or more of the coilelectrodes 8, 24 or 26 for delivering CV/DF shocks to the atria orventricles. It is recognized that alternate lead systems may besubstituted for the three lead system illustrated in FIG. 1A. While aparticular multi-chamber ICD and lead system is illustrated in FIG. 1A,methodologies included in the present invention may adapted for use withany single chamber, dual chamber, or multi-chamber ICD or pacemakersystem, subcutaneous implantable device, or other internal or externalcardiac monitoring device.

An external device 40 is shown in telemetric communication with ICD 10by an RF communication link 42. External device 40 is often referred toas a “programmer” because it is typically used by a physician,technician, nurse, clinician or other qualified user for programmingoperating parameters in ICD 10. External device 40 may be located in aclinic, hospital or other medical facility. External device 40 mayalternatively be embodied as a home monitor or a handheld device thatmay be used in a medical facility, in the patient's home, or anotherlocation. Operating parameters, such as sensing and therapy deliverycontrol parameters, may be programmed into ICD 10 using external device40.

External device 40 includes a processor 52, memory 53, user display 54,user interface 56 and telemetry circuitry 58. Processor 52 controlsexternal device operations and processes data and signals received fromICD 10. According to techniques disclosed herein, processor 52 receivessensing vector data obtained by ICD 10 and transmitted to telemetrycircuitry 58 from ICD 10. As described below in conjunction with FIG. 11, ICD 10 may be configured to store cardiac signal data associated withdetected atrial tachyarrhythmia episodes and transmit the cardiac signaldata to external device 40. Processor 52 provides user display 54 withat least a portion of the cardiac electrical signal data for generatinga display of the cardiac electrical signal detected as atrialtachyarrhythmia for observation and review by a clinician.

The user display 54 provides a display of the cardiac signal data andmay include a graphical user interface that facilitates programming ofone or more sensing parameters and/or atrial arrhythmia detectionparameters by a user interacting with external device 40. Externaldevice 40 may display other data and information relating to ICDfunctions to a user for reviewing ICD operation and programmedparameters as well as cardiac electrical signals or other physiologicaldata that is retrieved from ICD 10 during an interrogation session. Userinterface 56 may include a mouse, touch screen, or other pointingdevice, keyboard and/or keypad to enable a user to interact withexternal device 40 to initiate a telemetry session with ICD 10 forretrieving data from and/or transmitting data to ICD 10 and forselecting and programming desired sensing and therapy delivery controlparameters into ICD 10.

Telemetry circuitry 58 includes a transceiver and antenna configured forbidirectional communication with an implantable transceiver and antennaincluded in ICD 10. Telemetry circuitry 58 is configured to operate inconjunction with processor 52 for encoding and decoding transmitted andreceived data relating to ICD functions via communication link 42.Communication link 42 may be established between ICD 10 and externaldevice 40 using a radio frequency (RF) link such as BLUETOOTH®, Wi-Fi,Medical Implant Communication Service (MICS) or other RF bandwidth. Insome examples, external device 40 may include a programming head that isplaced proximate ICD 10 to establish and maintain a communication link,and in other examples external device 40 and ICD 10 may be configured tocommunicate using a distance telemetry algorithm and circuitry that doesnot require the use of a programming head and does not require userintervention to maintain a communication link.

It is contemplated that external device 40 may be in wired or wirelessconnection to a communications network via telemetry circuitry 58 fortransferring data to a remote database or computer to allow remotemanagement of the patient. Remote patient management systems may beconfigured to utilize the presently disclosed techniques to enable aclinician to review cardiac electrical signal data and atrialtachyarrhythmia episode data received from ICD 10 and to select andprogram control parameters transmitted to ICD 10. Reference is made tocommonly-assigned U.S. Pat. No. 6,599,250 (Webb et al.), U.S. Pat. No.6,442,433 (Linberg et al.), U.S. Pat. No. 6,418,346 (Nelson et al.), andU.S. Pat. No. 6,480,745 (Nelson et al.) for general descriptions andexamples of remote patient management systems that enable remote patientmonitoring and device programming. Each of these patents is incorporatedherein by reference in their entirety.

FIG. 1B is a conceptual diagram of a single-chamber ICD 10′ coupled toRV lead 16. The techniques disclosed herein may be implemented in asingle chamber ICD that is coupled only to a ventricular lead such as RVlead 16 for receiving cardiac electrical signals including at leastR-waves attendant to the ventricular depolarizations of heart 2.Electrodes 28 and 30 (and/or coil electrodes 24 and 26) may be used foracquiring cardiac electrical signals needed for performing atrialtachyarrhythmia detection as described herein without requiring anatrial sensing and pacing lead 11 as shown in FIG. 1A. R-waves sensedfrom cardiac electrical signals obtained by ICD 10′ are used fordetermining RR intervals (RRIs) between consecutively sensed R-waves fordetecting atrial tachyarrhythmia by a processor of ICD 10′ based atleast in part on an analysis of the RRIs. The single chamber ICD 10′ maybe configured to sense cardiac electrical signals from electrodes 24,26, 28 and/or 30, detect atrial tachyarrhythmia and provide an atrialtachyarrhythmia detection response such as storing atrialtachyarrhythmia episode data for transmission to external device 40(shown in FIG. 1A). Single chamber ICD 10′ may additionally beconfigured to deliver ventricular bradycardia pacing, detect ventriculartachyarrhythmias, and deliver anti-tachycardia pacing therapy andcardioversion/defibrillation shock therapies to the RV via electrodes24, 26, 28 and/or 30 carried by lead 16.

FIG. 1C is a conceptual diagram of a cardiac monitoring device 60 whichmay employ aspects of the atrial tachyarrhythmia detection techniquesdisclosed herein. Monitoring device 60 is shown implanted subcutaneouslyin the upper thoracic region of a patient's body 3 and displaced fromthe patient's heart 2. The housing 62 of cardiac monitor 60 (shownenlarged in scale compared to the patient's body 3) includes anon-conductive header module 64 attached to a hermetically sealedhousing 62. The housing 62 contains the circuitry of the cardiac monitor60 and is generally electrically conductive but may be covered in partby an electrically insulating coating. A first, subcutaneous, senseelectrode, A, is formed on the surface of the header module 64 and asecond, subcutaneous, sense electrode, B, is formed by at least aportion of the housing 62. For example, electrode B may be an exposedportion of housing 62 when housing 62 is coated by an electricallyinsulating coating. The conductive housing electrode B may be directlyconnected with the sensing circuitry.

An electrical feedthrough extends through the mating surfaces of theheader module 64 and the housing 62 to electrically connect the firstsense electrode A with sensing circuitry enclosed within the housing 62.The electrical signals attendant to the depolarization andre-polarization of the heart 2 are referred to as the cardiac electricalsignals and are sensed across the sense electrodes A and B and includeat least R-waves attendant to the ventricular depolarizations of heart2. The cardiac monitoring device 60 may be sutured to subcutaneoustissue at a desired orientation of its electrodes A and B to the axis ofthe heart 8 to detect and record the cardiac electrical signals in asensing vector A-B for subsequent processing and uplink telemetrytransmission to an external device 40 (shown in FIG. 1A).

In one embodiment, the spacing between electrodes A and B may range from60 mm to 25 mm. In other embodiments, the electrode spacing may rangefrom 55 mm to 30 mm, or from 55 mm to 35 mm. The volume of theimplantable cardiac monitoring device 60 may be three cubic centimetersor less, 1.5 cubic centimeters or less or any volume between three and1.5 cubic centimeters. The length of cardiac monitoring device 60 mayrange from 30 to 70 mm, 40 to 60 mm or 45 to 60 mm and may be any lengthbetween 30 and 70 mm. The width of a major surface such a cardiacmonitoring device 60 may range from 3 to 10 mm and may be any thicknessbetween 3 and 10 mm. The thickness of cardiac monitoring device 60 mayrange from 2 to 9 mm or 2 to 5 mm and may be any thickness between 2 and9 mm.

The sensing circuitry included in housing 62 is configured to detect theR-waves for monitoring for atrial tachyarrhythmia according to thetechniques disclosed herein. Such sensing circuitry may include apre-filter and amplifier, a rectifier, a sense amplifier, ananalog-to-digital filter, a comparator and/or other componentsconfigured to receive cardiac electrical signals. Aspects of a cardiacmonitoring device of the type that may employ atrial arrhythmiadetection techniques disclosed herein are generally disclosed in U.S.Publication No. 2015/0088216 (Gordon, et al.) and U.S. Pat. No.7,027,858 (Cao, et al.), both incorporated herein by reference in itsentirety.

In general, the hermetically sealed housing 62 includes a lithiumbattery or other power source, a processor and memory or other controlcircuitry that controls device operations and records arrhythmic cardiacelectrical signal episode data in memory registers, and a telemetrytransceiver antenna and circuit that receives downlink telemetrycommands from and transmits stored data in a telemetry uplink to theexternal device 40. The circuitry and memory may be implemented indiscrete logic or a micro-computer based system with A/D conversion ofsampled cardiac electrical signal amplitude values. One implantablecardiac monitor that can be modified in accordance with the presentlydisclosed techniques is described in U.S. Pat. No. 6,412,490 (Lee etal.), incorporated herein by reference in its entirety, as well as thecardiac monitors disclosed in any of the above-incorporated references.

FIG. 2 is a functional schematic diagram of an ICD, such as ICD 10 ofFIG. 1 . This diagram should be taken as illustrative of the type ofdevice with which the techniques disclosed herein may be embodied andnot as limiting. The example shown in FIG. 2 is a processor-controlleddevice, but the disclosed methods may also be practiced with other typesof devices such as those employing dedicated digital circuitry. In otherwords, processor 224 may include any combination of integratedcircuitry, discrete logic circuitry, analog circuitry, such as one ormore microprocessors, digital signal processors (DSPs), applicationspecific integrated circuits (ASICs), or field-programmable gate arrays(FPGAs). In some examples, processor 224 may include multiplecomponents, such as any combination of one or more microprocessors, oneor more DSPs, one or more ASICs, or one or more FPGAs, as well as otherdiscrete or integrated logic circuitry, and/or analog circuitry.

With regard to the electrode system illustrated in FIG. 1A, ICD 10 isprovided with a number of connection terminals for achieving electricalconnection to the leads 6, 11, and 16 and their respective electrodes.Housing 15 may be used as an indifferent electrode during unipolarstimulation or sensing. Electrodes 24, 26 and 8 may be selectivelycoupled to the high voltage output circuit 234 to facilitate thedelivery of high energy shocking pulses to the heart using one or moreof the coil electrodes 8, 24 and 26 and optionally the housing 15.

RA tip electrode 17 and RA ring electrode 21 may be coupled to atrialsense amplifier 204 for sensing atrial signals such as P-waves. RV tipelectrode 28 and the RV ring electrode 30 may be coupled to aventricular sense amplifier 200 for sensing ventricular signals. Theatrial sense amplifier 204 and the ventricular sense amplifier 200 maytake the form of automatic gain controlled amplifiers with adjustablesensitivity. ICD 10 and, more specifically, processor 224 mayautomatically adjust the sensitivity of atrial sense amplifier 204,ventricular sense amplifier 200 or both in response to detection ofoversensing in order to reduce the likelihood of oversensing of cardiacevents and/or non-cardiac noise.

Atrial sense amplifier 204 and ventricular sense amplifier 200 mayreceive timing information from pacer timing and control circuitry 212.For example, atrial sense amplifier 204 and ventricular sense amplifier200 may receive blanking period input, e.g., A_BLANK and V_BLANK,respectively, which indicates the amount of time the amplifiers are“turned off” in order to prevent saturation due to an applied pacingpulse or defibrillation shock. The general operation of the ventricularsense amplifier 200 and the atrial sense amplifier 204 may correspond tothat disclosed in U.S. Pat. No. 5,117,824 (Keimel, et al.), incorporatedherein by reference in its entirety. Whenever a signal received byatrial sense amplifier 204 exceeds an atrial sensitivity, a signal isgenerated on the P-out signal line 206. Whenever a signal received bythe ventricular sense amplifier 200 exceeds a ventricular sensitivity, asignal is generated on the R-out signal line 202. As described below, asignal on the R-out signal line 202, which may be referred to as aventricular sense event (Vs event) signal, may be received by processor224 and used for determining RRI differences.

Switch matrix 208 is used to select which of the available electrodes 8,17, 21, 24, 26, 28 and 30 are coupled to a wide band amplifier 210 foruse in digital signal analysis. Selection of the electrodes iscontrolled by the processor 224 via data/address bus 218. The selectedelectrode configuration may be varied as desired for the varioussensing, pacing, cardioversion and defibrillation functions of the ICD10. For example, while RV electrodes 28 and 30 are shown coupled tosense amplifier 200 and pace output circuit 216 suggesting dedicatedpace/sense electrodes and coil electrodes 24 and 26 are shown coupled toHV output circuit 234 suggesting dedicated CV/DV shock electrodes, it isrecognized that switching circuitry included in switch matrix 208 may beused to select any of the available electrodes in a sensing electrodevector, a pacing electrode vector, or a CV/DF shock vector as indicatedpreviously.

Signals from the electrodes selected for coupling to bandpass amplifier210 are provided to multiplexer 220, and thereafter converted tomulti-bit digital signals by A/D converter 222, for storage in memory226 under control of direct memory access circuit 228 via data/addressbus 218. Processor 224 may employ digital signal analysis techniques tocharacterize the digitized signals stored in memory 226 to recognize andclassify the patient's heart rhythm employing any of numerous signalprocessing methodologies for analyzing cardiac signals and cardiac eventwaveforms, e.g., P-waves and R-waves. One tachyarrhythmia detectionsystem is described in U.S. Pat. No. 5,545,186 (Olson et al.),incorporated herein by reference in its entirety.

It is to be understood that the circuitry shown in FIG. 2 may bemodified according to the particular device requirements. For example,the single chamber ICD 10′ of FIG. 1B may include the ventricular senseamplifier 200 and ventricular pace output circuit 216 and terminals forelectrically coupling to electrodes 24, 26, 28 and 30, while atrialsense amplifier 204, atrial pace output circuit 214 and terminals forelectrically coupling to electrodes 8, 17 and 21 may be omitted and/orcoupled to other electrodes. For example, sense amplifier 204 and/orpace output circuit 214 may be coupled to electrodes 24, 26, and/orhousing electrode 15.

Upon detection of an arrhythmia, an episode of cardiac signal data,along with sensed intervals and corresponding annotations of sensedevents, may be

stored in memory 226. The cardiac electrical signals sensed fromprogrammed sensing electrode pairs may be stored as EGM signals.Typically, a near-field sensing electrode pair includes a tip electrodeand a ring electrode located in the atrium or the ventricle, such as RAelectrodes 17 and 21 or RA electrodes 28 and 30. A far-field sensingelectrode pair includes electrodes spaced further apart such as any of:the defibrillation coil electrodes 8, 24 or 26 with housing 15; a tipelectrode 17 or 28 with housing 15; a tip electrode 17 or 28 with adefibrillation coil electrode 8, 24 or 26; or atrial tip electrode 17with ventricular ring electrode 30. The use of near-field and far-fieldEGM sensing of arrhythmia episodes is described in U.S. Pat. No.5,193,535 (Bardy), incorporated herein by reference in its entirety.Annotation of sensed events, which may be displayed and stored with EGMdata, is described in U.S. Pat. No. 4,374,382 (Markowitz), incorporatedherein by reference in its entirety.

FIG. 2 may suggest only two sensing channels, an atrial sensing channelincluding amplifier 204 and a ventricular sensing channel includingamplifier 200, in ICD 10, however it is recognized that the techniquesdisclosed herein may be applied to one or more cardiac electricalsignals acquired using any combination of the available electrodes. Insome examples, a first cardiac electrical signal is acquired between theICD housing 15 and RV coil electrode 24, a second cardiac electricalsignal is acquired between the RV coil electrode 24 and the SFV coilelectrode 26, and third cardiac electrical signal is acquired betweenthe RV tip electrode 28 and the RV ring electrode 30. All three signalsmay be collected and used by processor 224 for analyzing R-waves andRRIs and detecting atrial and/or ventricular arrhythmias. As discussedbelow in conjunction with FIG. 11 , at least two cardiac signals may bestored in memory 226 in the example of FIG. 2 , when a tachyarrhythmiaepisode is detected for later transmission by telemetry circuit 330.When atrial tachyarrhythmia is detected, with or without simultaneousdetection of ventricular tachyarrhythmia, the two signals may be storedhaving two different gain settings to provide two different signals fordisplay on external device 40. One signal displayed at a higher gain mayresult in R-wave clipping but enables relatively small amplitude P-wavesto be more readily observed, which enables any relationship between thedetected atrial and ventricular tachyarrhythmia (if present) to beobserved by a clinician through comparison of the two different signals.When ventricular tachyarrhythmia is detected without atrialtachyarrhythmia detection, two signals may be stored both having a gainsetting that avoids clipping of R-waves.

The telemetry circuit 330 includes a transceiver for receiving downlinktelemetry from and sending uplink telemetry to external device 40 usingantenna 332. Telemetry circuit 330 provides bi-directional telemetriccommunication with an external device 40 as described above.

ICD 10 may receive programmable operating parameters and algorithms viatelemetry circuit 330 for storage in memory 226 or other memory. Forexample, memory 226 may be any volatile, non-volatile, magnetic,optical, or electrical media, such as a random access memory (RAM),read-only memory (ROM), non-volatile RAM (NVRAM), electrically-erasableprogrammable ROM (EEPROM), flash memory, or any other digital media.Memory 226 may be accessed by processor 224 for controlling ICDfunctions. For example, cardiac rhythm detection parameters and therapycontrol parameters used by ICD 10 may be programmed via telemetrycircuit 330. Thus, memory 226 of IMD 10 may store program instructions,which may include one or more program modules, which are executable byprocessor 224. When executed by processor 224, such program instructionsmay cause processor 224 and IMD 10 to provide the functionality ascribedto them herein. The program instructions may be embodied in software,firmware and/or RAMware.

Data stored or acquired by ICD 10, including physiological signals orassociated data derived therefrom, results of device diagnostics, andhistories of detected arrhythmia episodes and delivered therapies, maybe retrieved from ICD 10 by the external device 40 following aninterrogation command received by telemetry circuit 330. Data to beunlinked to the external device and control signals for the telemetrycircuit 330 are provided by processor 224 via address/data bus 218.Received telemetry is provided to processor 224 via multiplexer 220.Numerous types of telemetry systems known for use in implantable medicaldevices may be implemented in ICD 10.

Other circuitry shown in FIG. 2 is illustrative of therapy deliverycircuitry that may be included in an ICD or other implantable medicaldevice employing the atrial arrhythmia detection technique disclosedherein when the device is configured for providing cardiac pacing,cardioversion and defibrillation therapies. For example, the pacertiming and control circuitry 212 may include programmable digitalcounters which control the basic time intervals associated with varioussingle, dual or multi-chamber pacing modes or anti-tachycardia pacingtherapies delivered in the atria or ventricles. Pacer timing and controlcircuitry 212 also sets the amplitude, pulse width, polarity or othercharacteristics of the cardiac pacing pulses under the control ofprocessor 224.

During pacing, escape interval counters within pacer timing and controlcircuitry 212 are reset upon sensing of R-waves or P-waves as indicatedby signals on lines 202 and 206, respectively. In accordance with theselected mode of pacing, pacing pulses are generated by atrial paceoutput circuit 214 and ventricular pace output circuit 216. The paceoutput circuits 214 and 216 are coupled to the desired electrodes forpacing via switch matrix 208. The escape interval counters are resetupon generation of pacing pulses, and thereby control the basic timingof cardiac pacing functions, including anti-tachycardia pacing.

The durations of the escape intervals are determined by processor 224via data/address bus 218. The value of the count present in the escapeinterval counters when reset by sensed R-waves or P-waves can be used tomeasure R-R intervals and P-P intervals for detecting the occurrence ofa variety of arrhythmias. Processor 224 may also track the number ofpacing pulses delivered, particularly the number of ventricular pacingpulses delivered, during predetermined time periods as a factor used inclassifying the cardiac electrical signal during the time period.

The processor 224 includes associated read-only memory (ROM) in whichstored programs controlling the operation of the processor 224 reside. Aportion of the random access memory (RAM) 226 may be configured as anumber of recirculating buffers capable of holding a series of measuredintervals for analysis by the processor 224 for predicting or diagnosingan arrhythmia.

In response to the detection of tachycardia, anti-tachycardia pacingtherapy can be delivered by loading a regimen from processor 224 intothe pacer timing and control circuitry 212 according to the type oftachycardia detected. In the event that higher voltage cardioversion ordefibrillation pulses are required, processor 224 activates thecardioversion and defibrillation control circuitry 230 to initiatecharging of the high voltage capacitors 246 and 248 via charging circuit236 under the control of high voltage charging control line 240. Thevoltage on the high voltage capacitors is monitored via a voltagecapacitor (VCAP) line 244, which is passed through the multiplexer 220.When the voltage reaches a predetermined value set by processor 224, alogic signal is generated on the capacitor full (CF) line 254,terminating charging. The defibrillation or cardioversion pulse isdelivered to the heart under the control of the pacer timing and controlcircuitry 212 by an output circuit 234 via a control bus 238. The outputcircuit 234 determines the electrodes used for delivering thecardioversion or defibrillation pulse and the pulse wave shape.

When ICD 10 is coupled to a RA lead 11 as shown in FIG. 1A, atrialelectrical stimulation therapies may be delivered in response todetecting atrial tachyarrhythmia using the techniques disclosed herein.In some examples, atrial pacing and/or an atrialcardioversion/defibrillation shock may be delivered to terminate asustained atrial tachyarrhythmia.

In some examples, the ICD 10 may be equipped with a patient notificationsystem 250. Any patient notification method known for use in implantablemedical devices may be used such as generating perceivable twitchstimulation or an audible sound. A patient notification system mayinclude an audio transducer that emits audible sounds including voicedstatements or musical tones stored in analog memory and correlated to aprogramming or interrogation operating algorithm or to a warning triggerevent as generally described in U.S. Pat. No. 6,067,473 (Greeninger etal.), incorporated herein by reference in its entirety. In someexamples, ICD 10 provides a response to an atrial tachyarrhythmiadetection by generating a patient notification via system 250 and/or aclinician notification using telemetry circuit 330. An atrialtachyarrhythmia response provided by ICD 10 may include determining anAF burden as the total combined duration of all detected AF episodesduring a predetermined monitoring time interval, e.g., 24 hours, andgenerating a patient notification and/or clinician notification when theAF burden exceeds a threshold.

FIGS. 3A and 3B are conceptual diagrams of an alternative ICD system 100that may be configured to detect AF according to the techniquesdisclosed herein. FIG. 3A is a front view of an extra-cardiovascular ICDsystem 100 implanted within patient 112. FIG. 3B is a side view of ICDsystem 100 implanted within patient 112. ICD system 100 includes an ICD110 connected to an extra-cardiovascular electrical stimulation andsensing lead 116. ICD system 100 may further include an intracardiacpacemaker 101 configured to deliver pacing pulses to a ventricular oratrial chamber.

ICD 110 includes a housing 115 that forms a hermetic seal that protectsinternal components of ICD 110. Internal device components may includecircuitry shown in FIG. 2 , such as sense amplifier(s), A/D converter,pacing output circuitry, high voltage output circuitry and a processorand memory and/or other control circuitry. The housing 115 of ICD 110may be formed of a conductive material, such as titanium or titaniumalloy. The housing 115 may function as a housing electrode (sometimesreferred to as a can electrode). In examples described herein, housing115 may be used as an active can electrode for use in deliveringcardioversion/defibrillation (CV/DF) shocks or other high voltage pulsesdelivered by HV charge circuit 236 (FIG. 2 ). In other examples, housing115 may be available for use in sensing cardiac signals or fordelivering unipolar, low voltage cardiac pacing pulses by a pacer outputcircuit in conjunction with lead-based cathode electrodes. In otherinstances, the housing 115 of ICD 110 may include multiple electrodes onan outer portion of the housing. The outer portion(s) of the housing 115functioning as an electrode(s) may be coated with a material, such astitanium nitride.

ICD 110 includes a connector assembly 117 (also referred to as aconnector block or header) that includes electrical feedthroughscrossing housing 115 to provide electrical connections betweenconductors extending within the lead body 118 of lead 116 and electroniccomponents included within the housing 115 of ICD 110. As describedabove in conjunction with FIG. 2 , housing 115 may house one or moreprocessors, memories, telemetry transceivers, sensing circuitry such assense amplifiers and analog-to digital converters, therapy deliverycircuitry such as pacer timing and control, CV/DF control, pace outputand HV output circuits and associated charging circuits, a switchmatrix, a data bus, one or more batteries or other power sources andother components for sensing cardiac electrical signals, detecting aheart rhythm, and controlling and delivering electrical stimulationpulses to treat an abnormal heart rhythm.

Lead 116 includes an elongated lead body 118 having a proximal end 127that includes a lead connector (not shown) configured to be connected toICD connector assembly 117 and a distal portion 125 that includes one ormore electrodes. In the example illustrated in FIGS. 3A and 3B, thedistal portion 125 of lead 116 includes defibrillation electrodes 124and 126 and pace/sense electrodes 128, 130 and 131. In some cases,defibrillation electrodes 124 and 126 may together form a defibrillationelectrode in that they may be configured to be activated concurrently.Alternatively, defibrillation electrodes 124 and 126 may form separatedefibrillation electrodes in which case each of the electrodes 124 and126 may be activated independently. In some instances, defibrillationelectrodes 124 and 126 are coupled to electrically isolated conductors,and ICD 110 may include switching mechanisms to allow electrodes 124 and126 to be utilized as a single defibrillation electrode (e.g., activatedconcurrently to form a common cathode or anode) or as separatedefibrillation electrodes, (e.g., activated individually, one as acathode and one as an anode or activated one at a time, one as an anodeor cathode and the other remaining inactive with housing 115 as anactive electrode).

Electrodes 124 and 126 (and in some examples housing 115) are referredto herein as defibrillation electrodes because they are utilized,individually or collectively, for delivering high voltage stimulationtherapy (e.g., cardioversion or defibrillation shocks). Electrodes 124and 126 may be elongated coil electrodes and generally have a relativelyhigh surface area for delivering high voltage electrical stimulationpulses compared to low voltage pacing and sensing electrodes 28, 30 and31. However, electrodes 124 and 126 and housing 115 may also be utilizedto provide pacing functionality, sensing functionality or both pacingand sensing functionality in addition to or instead of high voltagestimulation therapy. In this sense, the use of the term “defibrillationelectrode” herein should not be considered as limiting the electrodes124 and 126 for use in only high voltage cardioversion/defibrillationshock therapy applications. Electrodes 124 and 126 may be used in apacing electrode vector for delivering extra-cardiovascular pacingpulses such as ATP pulses, post-shock pacing or other pacing therapiesand/or in a sensing vector used to sense cardiac electrical signals fordetecting atrial and ventricular arrhythmias, referred to generally as“cardiac events”, including AF, VT and VF.

Electrodes 128, 130 and 131 are relatively smaller surface areaelectrodes for delivering low voltage pacing pulses and for sensingcardiac electrical signals. Electrodes 128, 130 and 131 are referred toas pace/sense electrodes because they are generally configured for usein low voltage applications, e.g., used as either a cathode or anode fordelivery of pacing pulses and/or sensing of cardiac electrical signals.Electrodes 124, 126,128, 130 and/or 131 may be used to acquire cardiacelectrical signals used for AF detection according to the techniquesdisclosed herein.

Lead 16 extends subcutaneously or submuscularly over the ribcage 132medially from the connector assembly 127 of ICD 110 toward a center ofthe torso of patient 112, e.g., toward xiphoid process 120 of patient112. At a location near xiphoid process 120, lead 116 bends or turns andextends superiorly within anterior mediastinum 136 in a substernalposition. Lead 116 of system 100 is implanted at least partiallyunderneath sternum 122 of patient 112.

Anterior mediastinum 136 may be viewed as being bounded laterally bypleurae, posteriorly by pericardium 138, and anteriorly by sternum 122.In some instances, the anterior wall of anterior mediastinum 136 mayalso be formed by the transversus thoracis muscle and one or more costalcartilages. Anterior mediastinum 136 includes a quantity of looseconnective tissue (such as areolar tissue), adipose tissue, some lymphvessels, lymph glands, substernal musculature, small side branches ofthe internal thoracic artery or vein, and the thymus gland. In oneexample, the distal portion 125 of lead 116 extends along the posteriorside of sternum 122 substantially within the loose connective tissueand/or substernal musculature of anterior mediastinum 136.

A lead implanted such that the distal portion 125 is substantiallywithin anterior mediastinum 136 may be referred to as a “substernallead.” In the example illustrated in FIGS. 3A and 3B, lead 116 extendssubstantially centered under sternum 122. In other instances, however,lead 116 may be implanted such that it extends in a position that isoffset laterally from the center of sternum 122. In some instances, lead116 may extend laterally such that distal portion 125 of lead 116 isunderneath/below the ribcage 132 in addition to or instead of sternum122. In other examples, the distal portion 125 of lead 116 may beimplanted in other extra-cardiovascular, intra-thoracic locations,including the pleural cavity or around the perimeter of and adjacent tobut typically not within the pericardium 138 of heart 102.

In other examples, lead 116 may remain outside the thoracic cavity andextend subcutaneously or submuscularly over the ribcage 132 and/orsternum 122. The path of lead 116 may depend on the location of ICD 110,the arrangement and position of electrodes carried by the lead distalportion 125, and/or other factors.

Electrical conductors (not illustrated) extend through one or morelumens of the elongated lead body 118 of lead 116 from the leadconnector at the proximal lead end 127 to electrodes 124, 126, 128, 130and 131 located along the distal portion 125 of the lead body 118. Thelead body 118 of lead 116 may be formed from a non-conductive material,including silicone, polyurethane, fluoropolymers, mixtures thereof, andother appropriate materials, and shaped to form one or more lumenswithin which the one or more conductors extend. However, the techniquesdisclosed herein are not limited to such constructions or to anyparticular lead body design.

The elongated electrical conductors contained within the lead body 118are each electrically coupled with respective defibrillation electrodes124 and 126 and pace/sense electrodes 128, 130 and 131. Each of pacingand sensing electrodes 128, 130 and 131 are coupled to respectiveelectrical conductors, which may be separate respective conductorswithin the lead body. The respective conductors electrically couple theelectrodes 124, 126, 128, 130 and 131 to circuitry, such as a switchmatrix or other switching circuitry for selection and coupling to asense amplifier or other cardiac event detection circuitry and/or to atherapy output circuit, e.g., a pacing output circuit or a HV outputcircuit for delivering CV/DF shock pulses. Connections between electrodeconductors and ICD circuitry is made via connections in the connectorassembly 117, including associated electrical feedthroughs crossinghousing 115. The electrical conductors transmit therapy from an outputcircuit within ICD 110 to one or more of defibrillation electrodes 124and 126 and/or pace/sense electrodes 128, 130 and 131 and transmitsensed electrical signals from one or more of defibrillation electrodes124 and 126 and/or pace/sense electrodes 128, 130 and 131 to the sensingcircuitry within ICD 110.

ICD 110 may obtain electrical signals corresponding to electricalactivity of heart 102 via a combination of sensing vectors that includecombinations of electrodes 128, 130, and/or 131. In some examples,housing 115 of ICD 110 is used in combination with one or more ofelectrodes 128, 130 and/or 131 in a sensing electrode vector. ICD 110may even obtain cardiac electrical signals using a sensing vector thatincludes one or both defibrillation electrodes 124 and/or 126, e.g.,between electrodes 124 and 126 or one of electrodes 124 or 126 incombination with one or more of electrodes 128, 130, 131, and/or thehousing 115.

ICD 110 analyzes the cardiac electrical signals received from one ormore of the sensing vectors to monitor for abnormal rhythms, such as AF,VT and VF. ICD 110 generates and delivers electrical stimulation therapyin response to detecting a ventricular tachyarrhythmia (e.g., VT or VF).ICD 110 may deliver ATP in response to VT detection, and in some casesmay deliver ATP prior to a CV/DF shock or during high voltage capacitorcharging in an attempt to avert the need for delivering a CV/DF shock.ICD 110 may deliver a CV/DF shock pulse when VF is detected or when VTis not terminated by ATP.

In other examples, lead 16 may include less than three pace/senseelectrodes or more than three pace/sense electrodes and/or a singledefibrillation electrode or more than two electrically isolated orelectrically coupled defibrillation electrodes or electrode segments.The pace/sense electrodes 28, 30 and/or 31 may be located elsewherealong the length of lead 16. For example, lead 16 may include a singlepace/sense electrode 30 between defibrillation electrodes 24 and 26 andno pace/sense electrode distal to defibrillation electrode 26 orproximal defibrillation electrode 24. Various example configurations ofextra-cardiovascular leads and electrodes and dimensions that may beimplemented in conjunction with the AF detection techniques disclosedherein are described in commonly-assigned U.S. patent application Ser.No. 14/519,436, U.S. patent application Ser. No. 14/695,255 andprovisionally-filed U.S. Pat. Application No. 62/089,417, all of whichare incorporated herein by reference in their entirety.

ICD 110 is shown implanted subcutaneously on the left side of patient112 along the ribcage 132. ICD 110 may, in some instances, be implantedbetween the left posterior axillary line and the left anterior axillaryline of patient 112. ICD 110 may, however, be implanted at othersubcutaneous or submuscular locations in patient 112. For example, ICD110 may be implanted in a subcutaneous pocket in the pectoral region. Inthis case, lead 116 may extend subcutaneously or submuscularly from ICD110 toward the manubrium of sternum 122 and bend or turn and extendinferior from the manubrium to the desired location subcutaneously orsubmuscularly. In yet another example, ICD 110 may be placedabdominally.

In some patients, an intracardiac pacemaker 101 may be present in theright ventricle, right atrium or along the left ventricle. Pacemaker 101may be configured to deliver pacing pulses in the absence of sensedintrinsic heart beats, in response to detecting VT, or according toother pacing therapy algorithms. For example, pacemaker 101 may beimplanted in the right ventricle of the patient for providing singlechamber ventricular pacing. The techniques disclosed herein forclassifying a cardiac signal may be utilized in the presence ofventricular pacing delivered by ICD 110 and/or by an intracardiacpacemaker such as pacemaker 101. Pacemaker 101 may generally correspondto the intracardiac pacemaker disclosed in U.S. Pat. No. 8,923,963(Bonner, et al.), incorporated herein by reference in its entirety. ICD110 may be configured to detect pacing pulses delivered by pacemaker101. The frequency of pacing pulses delivered by pacemaker 101 may be afactor determined in classifying a cardiac electrical signal time periodfor AF detection purposes.

Pacemaker 101 may have limited processing power and therapy deliverycapacity compared to ICD 110 such that the advanced cardiac rhythmdetection techniques disclosed herein may be implemented in ICD 110rather than in pacemaker 101. As such, the methods disclosed herein aredescribed in conjunction with ICD 10, 10′ or ICD 110 or cardiacmonitoring device 60. These techniques, however, are not to beconsidered limited to being implemented in an ICD or subcutaneous orexternal cardiac monitor. Aspects of the AF detection techniquesdisclosed herein may be implemented in pacemaker 101, all or in part.

FIG. 4 is a schematic diagram of methods used for detecting cardiacevents by a medical device, such as ICD 10, ICD 10′, cardiac monitoringdevice 60, or ICD 110, according to one example. Single chamber deviceshave been designed to detect AF using a ventricular EGM signal.Illustrative methods and devices for detecting AF using a ventricularEGM signal are generally described in commonly assigned U.S. patentapplication Ser. Nos. 14/520,798, 14/520,938 and 14/520,847 (Cao etal.), all of which are incorporated herein by reference in theirentirety. R-waves attendant to the ventricular depolarization are sensedfrom the ventricular EGM signal and used to determine RRIs, i.e.,intervals between successive R-waves. Successive RRI differences aredetermined by subtracting an RRI from an immediately preceding RRI. Ananalysis of a Lorenz plot of the successive RRI differences may revealan RRI variability pattern that is typical of AF.

Methods for detecting atrial arrhythmias based on the irregularity ofventricular cycles determined from RRI differences that exhibitdiscriminatory signatures when plotted in a Lorenz scatter plot, such asthe plot shown in FIG. 4 , are generally disclosed by Ritscher et al. inU.S. Pat. No. 7,031,765, incorporated herein by reference in itsentirety. Other methods are generally disclosed by Sarkar, et al. inU.S. Pat. No. 7,623,911 and in U.S. Pat. No. 7,537,569 and by Houben inU.S. Pat. No. 7,627,368, all of which patents are also incorporatedherein by reference in their entirety.

In the following description, AF detection techniques are described withreference to the circuitry of FIG. 2 and ICD 10 of FIG. 1A. It is to beunderstood, however, that the methods and techniques of the descriptionsthat follow may be implemented in ICD 10′ of FIG. 1B, ICD 110 of FIGS.3A and 3B or a cardiac monitoring device such as the device of FIG. 1C,all of which devices may include a processor, memory and sensingcircuitry, as generally described in conjunction with FIG. 2 , forperforming these AF detection techniques.

In order to determine whether AF is occurring, the processor 224 (FIG. 2) may determine differences between RRIs based on sensed R-waves (e.g.,R OUT signal line 202 in FIG. 2 ). Processor 224 may make the decisionas to whether an AF event is occurring based at least in part on theresulting pattern or signature of RRI differences. As described below,when the resulting signature of RRI differences acquired over apredetermined time period indicates AF is occurring, the cardiac signaltime period is classified as AF. AF is detected when a required numberof time periods are classified as AF. Techniques disclosed herein may beutilized as part of an overall tachyarrhythmia detection anddiscrimination algorithm implemented in ICD 10 or the other devicesdescribed above or in other implantable or external cardiac devices,such as an intracardiac pacemaker, a leadless pacemaker or an externaldevice.

The concept of using a signature of RRI differences for detecting AF isillustrated by the generation of a Lorenz scatter plot as shown in FIG.4 . Processor 224 determines the differences between consecutive pairsof RR-intervals (δRRs) which can be plotted for a time series of RRIs.The Lorenz plot 150 is a Cartesian coordinate system defined by δRR_(i)along the x-axis 152 and δRR_(i-1) along the y-axis 154. As such, eachplotted point in a Lorenz plot is defined by an x-coordinate equalingδRR_(i) and a y-coordinate equaling δRR_(i-1). δRR_(i) is the differencebetween the i^(th) RRI and the previous RRI, RRI_(i-1). δRR_(i-1) is thedifference between RRI_(i-1) and the previous RRI, RRI_(i-2).

As such, each data point plotted on the Lorenz plot 150 represents anRRI pattern relating to three consecutive RRIs: RRI_(i), RRI_(i-1) andRRI_(i-2), measured between four consecutively sensed R-waves. RRIinformation is not limited to detection of R-waves and determination ofRRIs. The terms RRI and δRR_(i) as used herein refer generally to ameasurement of ventricular cycle length (VCL) and the difference betweentwo consecutive VCL measurements, respectively, whether the VCLmeasurements were derived from a series of sensed R-waves from a cardiacelectrical signal or a series of ventricular cycle event detections madefrom another physiological signal (e.g., a peak pressure determined froma pressure signal). For the sake of illustration, the methods describedherein refer to R-wave detections for performing VCL measurements andthe determination of (δRR_(i), δRR_(i-1)) points.

As illustrated in FIG. 4 , a series of R-waves 170 (represented byvertical bars) are sensed and in order to plot a point on the Lorenzplot area 150, a (δRR_(i), δRR_(i-1)) point is determined by determiningsuccessive RRIs determined from the sensed R-waves 170. In the exampleshown, a first series 172 of three consecutive RRIs (RRI_(i-2),RRI_(i-1) and RRI_(i)) provides the first data point 155 on the Lorenzplot area 150. δRR_(i-1), which is the difference between RRI_(i-2) andRRI_(i-1) is near 0. δRR_(i), the difference between the RRI_(i-1) andRRI_(i), is a positive change. Accordingly, a (δRR_(i), δRR_(i-1)) point155 having a y-coordinate near 0 and a positive x-coordinate is plottedin the Lorenz plot 150, representing the first series 172 of four sensedR-waves (three RRIs).

The next series 174 of three RRIs provides the next (δRR_(i), δRR_(i-1))point 156 having a negative x-coordinate (the last RRI of series 174being less than the immediately preceding RRI) and a positivey-coordinate (the middle RRI of series 174 being longer than the firstRRI of series). This process of plotting (δRR_(i), δRR_(i-1)) pointscontinues with the three cycle series 176 providing data point 158 andso on.

FIG. 5 is a diagram of a two-dimensional histogram representing a Lorenzplot area 150 used in the techniques disclosed herein for detectingatrial tachyarrhythmia. Generally, the Lorenz plot area 150 shown inFIG. 4 is numerically represented by a two-dimensional histogram 180having predefined ranges 184 and 186 in both positive and negativedirections for the δRR₁ coordinates (corresponding to x-axis) andδRR_(i-1) coordinates (corresponding to y-axis), respectively. Thetwo-dimensional histogram 180 is divided into bins 188 each having apredefined range of δRR_(i) and δRR_(i-1) values. In one example, thehistogram range might extend from −1200 ms to +1200 ms for both δRR_(i)and δRR_(i-1) values, and the histogram range may be divided into binsextending for a range of 7.5 ms in each of the two dimensions resultingin a 160 bin×160 bin histogram 180. The successive RRI differencesdetermined over a classification time period are used to populate thehistogram 180. Each bin stores a count of the number of (δRR_(i),δRR_(i-1)) data points falling into each respective bin range. The bincounts may then be used by processor 224 in determining RRI variabilitymetrics and patterns for detecting a cardiac rhythm type.

An RRI variability metric is determined from the histogram bin counts.Generally, the more histogram bins that are occupied, or the more sparsethe distribution of (δRR_(i), δRR_(i-1)) points, the more irregular theVCL is during the data acquisition time period. As such, one metric ofthe RRI variability that can be used for detecting AF, which isassociated with highly irregular VCL, may take into account the numberof histogram bins that have a count of at least one, which is referredto as an “occupied” bin. In one example, an RRI variability metric fordetecting AF, referred to as an AF score, is determined by processor 224as generally described in the above-incorporated '911 patent. Briefly,the AF score may be defined by the equation:AF Score=Irregularity Evidence−Origin Count−PAC Evidence

wherein Irregularity Evidence is the number of occupied histogram binsoutside a Zero Segment 188 defined around the origin of the Lorenz plotarea. During normal sinus rhythm or highly organized atrial tachycardia,nearly all points will fall into the Zero Segment 188 because ofrelatively small, consistent differences between consecutive RRIs. Ahigh number of occupied histogram bins outside the Zero segment 188 istherefore positive evidence for AF.

The Origin Count is the number of points in the Zero Segment 188 definedaround the Lorenz plot origin. A high Origin Count indicates regularRRIs, a negative indicator of AF, and is therefore subtracted from theIrregularity Evidence term. In addition, a regular PAC evidence scoremay be computed as generally described in the above-incorporated '911patent. The regular PAC evidence score is computed based on a clustersignature pattern of data points that is particularly associated withpremature atrial contractions (PACs) that occur at regular couplingintervals and present regular patterns of RRIs, e.g., associated withbigeminy (short-short-long RRIs) or trigeminy (short-short-short-longRRIs). In other embodiments, the AF score and/or other RRI variabilityscore for classifying an atrial rhythm may be determined by processor224 as described in any of the above-incorporated '765, '316, '911, '569and '368 patents. Methods for rejecting noise in determining Lorenz plotpoints and an AF score are generally disclosed in U.S. Pat. No.8,639,316 (Sarkar, et al.), incorporated herein by reference in itsentirety. Methods for adjusting the AF score based on the presence ofectopy may be used in the techniques disclosed herein and are generallydisclosed in U.S. Pat. No. 8,977,350 (Sarkar, et al.), incorporatedherein by reference in its entirety. Other techniques that may be usedin computing an AF score are generally disclosed in U.S. patentapplication Ser. Nos. 14/695,135, 14/695,156, 14/695,171 and 14/695,111(Sarkar, et al.), all filed on Apr. 24, 2015 and incorporated herein byreference in their entirety.

The AF score is compared to an AF score threshold for classifying apredetermined time period of a cardiac signal as AF or non-AF based onthe RRI analysis. The AF score threshold may be selected and optimizedbased on historical clinical data of selected patient populations orhistorical individual patient data, and the optimal AF score thresholdsetting may vary from patient to patient. In an illustrative example,the AF score may have a possible range of 0 to 100. The AF scorethreshold may be set between 25 and 75. If the AF score meets or crossesan AF score threshold, the time period over which the RRIs werecollected, and thus the cardiac signal occurring within the time period,is classified as an AF time period. The AF score threshold may beadjusted after classifying at least one time period of the cardiacsignal as being AF and the adjusted AF score threshold may be used forclassifying subsequent time periods, which may lead to an AF detection.The adjusted AF score threshold is less than the initial AF scorethreshold and may have a value ranging from 19 to 57 in the examplegiven above where the maximum AF score is 100 and the initial AF scorethreshold is at least 26 and not more than 75. Thus, the adjusted AFscore threshold may be between 65-85% of the initial AF score thresholdand, in some instances between 70-75% of the initial AF score.

An AF detection is made when a threshold number of time periods areclassified as AF. In one example, a single n-second or n-minute timeperiod classified as AF based on the AF score meeting the AF scorethreshold may result in an AF detection. In other examples, a highernumber of time periods may be required to be classified as being AFbefore detecting the heart rhythm as AF.

The processor 224 provides a response to the AF detection, which mayinclude withholding, adjusting or delivering a therapy (e.g.,withholding ATP or shock therapy for treating a ventriculartachyarrhythmia or delivering an atrial anti-tachyarrhythmia therapy ifavailable), storing cardiac signal data that can be later retrieved by aclinician using external device 40, triggering patient notificationsystem 250, transmitting data via telemetry circuit 330 to alert aclinician, and/or triggering other signal acquisition or analysis.

The RRI analysis may continue to be performed by processor 224 after anAF detection is made to fill the histogram during the next n-seconddetection time period. After each detection time period, the AF scoremay be re-determined and the histogram bins are re-initialized to zerofor the next detection time period. The new AF score (or other RRIvariability metrics) determined at the end of each detection time periodmay be used to determine if the AF episode is sustained or terminatedafter the initial AF detection is made.

FIG. 6 is a flowchart 300 of a method for determining a factor forclassifying time periods for detecting atrial arrhythmias according toone example. Flow chart 300 and other flow charts presented herein areintended to illustrate the functional operation of ICD 10 or anotherdevice performing the disclosed methods, and should not be construed asreflective of a specific form of software, firmware or hardwarenecessary to practice the methods. It is believed that the particularform of software will be determined primarily by the particular systemarchitecture employed in the device and by the particular detection andtherapy delivery methodologies employed by the device. Providingsoftware, firmware and/or hardware to accomplish the techniquesdisclosed herein in the context of any modern medical device, given thedisclosure herein, is within the abilities of one of skill in the art.

Methods described in conjunction with flow charts presented herein maybe implemented in a non-transitory computer-readable medium thatincludes instructions for causing a programmable processor, such asprocessor 224, to carry out the methods described. A “computer-readablemedium” includes but is not limited to any volatile or non-volatilemedia, such as a RAM, ROM, CD-ROM, NVRAM, EEPROM, flash memory, and thelike. The instructions may be implemented as one or more softwaremodules, which may be executed by themselves or in combination withother software.

As illustrated in FIG. 6 , the processor 224 identifies ventricularevents at block 301, such as R-waves based on Rout signal line 202, andidentifies the ventricular event as being either an intrinsic sensedevent Vs or a paced event Vp resulting from pacing being delivered byICD 10 or 10′ (or by ICD 110 or pacemaker 101). Depending upon thenumber of RR intervals chosen for determining RR interval differences,processor 224 determines whether a predetermined number of events,either a ventricular pacing event Vp or intrinsic ventricular sensedevent VS, have been identified at block 302. For example, according toone example, if the desired number of RR intervals for determiningsuccessive RR interval differences is three, the predetermined number ofevents utilized in block 302 would be four events, with the four eventsforming a sensing window. If the predetermined number of events has notbeen reached, “No” branch of block 302, processor 224 determines thenext ventricular event, at block 301, and the process is repeated.

Once the predetermined number of events are identified, “Yes” branch ofblock 302, an event window is identified based on the four events, atblock 304, and a determination may be made as to whether the number ofthe events in the event window that are ventricular pace Vp events isless than or equal to a predetermined pacing event threshold at block306. For example, according to one example, the pacing event thresholdis set as one so that processor 224 determines whether one or less ofthe identified events in the event window are ventricular pace events.If the number of identified events in the event window that areventricular pace Vp events is not less than or equal to, i.e., isgreater than, the predetermined pacing event threshold, “No” branch ofblock 306, processor 224 identifies the next event at block 301, and theprocess is repeated.

If the number of events in the event window that are ventricular pace Vpevents is less than or equal to the predetermined pacing eventthreshold, “Yes” branch of block 306, processor 224 determines whethereach of the RR intervals associated with the events in the current eventwindow are greater than a predetermined interval threshold at block 308.For example, according to one example, processor 224 determines whethereach of the RR intervals associated with the events in the event windowis greater than 220 milliseconds. If each of the RR intervals associatedwith the events in the event window are not greater than thepredetermined interval threshold, “No” branch of block 308, processor224 identifies the next event at block 301, and the process is repeatedusing the next identified event and the resulting next event window.

If each of the RRIs associated with the events in the event window aregreater than the predetermined interval threshold, “Yes” branch of block308, processor 224 determines differences between successive RRIsassociated with the identified events in the event window, block 310.Once the RRI differences for the current event window have beendetermined at block 308, to populate a Lorenz plot histogram asdescribed above, processor 224 determines whether a predetermined timeperiod has expired at block 312. Processor 224 may set a timer orcounter to control acquisition of RRI differences over a predeterminedtime period at the onset of the method of flow chart 300. In oneexample, the predetermined time period may be set to two minutes. Inother examples, the predetermined time period may be between one to fiveminutes. If the time period has not expired, “No” branch of block 312,processor 224 returns to block 301 to identify the next ventricularevent and the process is repeated using the next event and the resultingnext event window.

Once the timer has expired, “Yes” branch of block 312, processor 224determines an AF score at block 314, based on the determined RRIdifferences during the predetermined time period, e.g., two minutes. TheAF score may be determined as described above with respect to FIG. 5and/or the incorporated patents. As described below in conjunction withFIG. 7 , the determined AF score for the predetermined time period isused to classify the time period (and thus the cardiac signal during thetime period) as an AF time period, a non-AF time period or anunclassified time period. The stored RRI differences are then clearedand all counters and timers reset at block 316. A timer set to thepredetermined time period, e.g., two minutes, is reset. Processor 224identifies the next ventricular event at block 300, and the process isrepeated for the next time period using the next identified events andthe next event windows.

FIG. 7 is a flowchart 400 of a method for classifying a predeterminedtime period according to one example. The example described in flowchart400 of FIG. 7 will be described in the context of having predeterminedtime periods that are two minutes in length. However, the techniquesdescribed in FIG. 7 or elsewhere throughout this description can be forpredetermined time periods that are longer or shorter than two minutes.Once the predetermined time period, e.g., a two minute time period, hasexpired and a Lorenz plot has been populated with a point associatedwith each determined RR interval difference determined based on theintervals in each event window occurring during the two minute timeperiod as described in conjunction with FIGS. 4, 5 and 6 , processor 224determines whether to classify the time period as being either an AFtime period, a non-AF time period, or an unclassified time period (i.e.,the time period can neither be classified as an AF time period nor anon-AF time period). For example, processor 224 may analyze one or moreof several factors, in any combination or particular order, to make thedetermination.

As described in conjunction with the example of FIG. 7 , among thefactors that may be analyzed for classifying the two minute time periodare the number of valid RRI difference pairs, RRI lengths, number ofpaced beats, number of short intervals, presence of oversensing ofventricular events, presence of T-wave oversensing, detection of aventricular tachyarrhythmia (e.g., SVT, VT or VF or more generallyreferred to as “other episodes”), and the AF score. However, processor224 may analyze only a subset of these factors and/or include otherfactors.

Processor 224 may determine the number of RRI difference pairs acquiredduring the two minute time period at block 401, where each RRIdifference pair represents one point of the Lorenz plot. A determinationis then made as to whether the total number of RRI difference pairsformed during the two minute time period is greater than an intervalpair threshold at block 402. According to one example, a thresholdnumber of RRI difference pairs is set at 30, though other thresholds maybe used. If the total number of RRI difference pairs (representing threeconsecutive RRIs) during the two minute time period is less than thethreshold, “Yes” branch at block 402, the two minute time period isdetermined to be unclassified at block 404. In the example describedabove in which the threshold is set at 30, the “Yes” branch of block 402means that less than 30 RRI difference pairs were determined during thetwo minute time period, resulting in the Lorenz plot histogram beingpopulated with less than 30 points. An AF scored determined from fewerthan the threshold number of RRI difference pairs may not yield areliable AF score for the predetermined time period and therefore is notused to classify the time period as either AF or non-AF.

If the number of RRI difference pairs that are formed during the twominute time period is not less than the interval pair threshold (30 inthe example above), “No” branch of block 402, the interval pairs factorfor classifying the time period as either AF or non-AF based on an AFscore determined from the RRI difference pairs is satisfied. In otherwords, using the example above, 30 or RRI difference pairs weredetermined during the two minute time period, resulting in the Lorenzplot histogram being populated with 30 or more points. The number of RRIdifference pairs obtained during the pre-determined time period isadequate to reliably classify the time period as AF or non-AF based onthe AF score.

According to another example, processor 224 may additionally oralternatively determine, at block 410, the total number of RRIs duringthe predetermined time period that were determined to be less than theinterval threshold applied at block 308 of flow chart 300. If more thana threshold number of RRIs, e.g., more than a predetermined number ofRRIs or a predetermined percentage of the total number of RRIs occurringduring the two-minute time period, are less than the interval threshold,“Yes” branch at block 412, the two minute time period is determined tobe unclassified, at block 404. If the number of RRIs less than theinterval threshold does not reach or exceed a predetermined number, e.g.if less than 10 RRIs are less than the interval threshold during the twominute time period, this RRI length factor is determined not to besatisfied at block 412 (“No” branch of block 412) for classifying thepredetermined time interval as unclassified. Based on at least thisfactor, a classification of either AF or non-AF based on the AF score iswarranted.

In order to classify the two minute time period as either AF or non-AF,processor 224 may determine, at block 414, a short interval count of thetotal number of RRIs from all of the event windows obtained during thetwo minute time period that were less than or equal to a predeterminedshort interval threshold, such as 120 milliseconds or 130 milliseconds,for example. Processor 224 determines whether the short interval countis greater than a short interval threshold, at block 416, such as 5short intervals for example. Too many short intervals during the twominute time period indicates the possibility of ventricular oversensingof non-physiological signals such as EMI or lead noise due to leadfracture. In this situation, the RRIs may be unreliable for determiningan AF score and classifying the time period as AF or non-AF based on theAF score.

If the determined short interval count is greater than the shortinterval count threshold, “Yes” branch at block 416, the two minute timeperiod is determined to be unclassified at block 404. On the other hand,if the short interval count is less than the short interval countthreshold, the time period can be classified based on the AF score, “No”branch at block 416. This short interval count factor minimizes false AFdetection due to lead noise oversensing.

Processor 224 may additionally or alternatively determine the number ofevents identified during the total two minute time period within all ofthe event windows that were determined to be ventricular pace Vp eventsat block 418. A determination is made as to whether the determinednumber of ventricular pace Vp events identified during all event windowsof the two minute time period is greater than a total ventricular paceVp event threshold at block 420. According to one example, the totalventricular pace Vp threshold is set as 30 ventricular pace Vp events,though other thresholds may be used.

If the number of ventricular pace Vp events during the two minute timeperiod is greater than the total ventricular pace Vp event threshold,“Yes” branch of block 420, processor 224 classifies the two minute timeperiod as unclassified at block 404. Ventricular pacing pulses mayinclude bradycardia pacing pulses and/or ATP pacing pulses and may bedelivered by ICD 10, 10′ or 110 or by another implanted device, e.g.,pacemaker 110. On the other hand, if the determined number ofventricular pace Vp events is not greater than Vp event threshold, “No”branch at block 420, the two minute time period is not classified asunclassified; a classification of AF or non-AF based on the AF score maybe made as long as no other factors lead to a determination of the timeperiod being unclassified.

Processor 224 may be configured to simultaneously evaluate R-waves andRRIs for detecting supraventricular tachycardia (SVT), VT and VF whilethe AF detection algorithms described herein are operating. ICD 10 maybe configured to deliver therapies such as ATP in response to detectingVT. As such, if a ventricular tachyarrhythmia detection, e.g., SVT, VTor VF detection, is being made during or at the expiration of thecurrent time period, as determined at block 421, the current time periodis determined to be unclassified at block 404. If no other episodedetections are being made, the process may advance to block 422.

The processor 224 may additionally or alternatively determine whetherventricular event oversensing caused by noise was detected during thetwo minute time period, at block 422. Detection of oversensing may beperformed by processor 224 using an implemented oversensing detectionscheme, such as the oversensing detection methods generally described inU.S. Pat. No. 7,333,855 to Gunderson et. al., incorporated herein byreference in its entirety. If oversensing detection criteria were met orwere in the process of being met during the two minute time period,“Yes” branch of block 422, the two minute time period is determined tobe unclassified at block 404. Detection of oversensing indicates thatthe RRIs may be unreliable for determining an AF score and classifyingthe time period based on the AF score. If a detection of oversensing wasnot made or not in the process of being made during the two minute timeperiod, “No” branch of block 422, an AF or non-AF classification may bemade based on the AF score as long as other factors do not lead to thetime period be classified as unclassified.

Processor 224 may determine whether T-wave oversensing occurred duringthe two minute time period at block 424. The determination of T-waveoversensing may be performed by ICD 10 using an implemented T-waveoversensing detection scheme, such as the T-wave oversensingdetermination described in U.S. Pat. No. 7,831,304 to Gillberg, et al.,incorporated herein by reference in its entirety. If a determination ofT-wave oversensing was made or was in process during the two minute timeperiod, “Yes” branch of block 424, the T-wave oversensing factor issatisfied as an indication of the two minute time period beingunclassified. Processor 224 classifies the two minute time period asunclassified at block 404. If a determination of T-wave oversensing wasnot made or was not in the process of being made during the two minutetime period, “No” branch of block 424, the T-wave oversensing factor isnot satisfied. Processor 224 advances to block 426 to classify the timeperiod based on the AF score.

In this way, ICD 10 (or ICD 10′, ICD 110, or cardiac monitoring device60) may analyze the cardiac electrical signal over the two minute timeperiod for one or more of the described factors, which if satisfiedwould cause the two minute time period to be classified as“unclassified.” In other words, ICD 10, ICD 110, or other device mayanalyze all of the described factors or only a subset of the describedfactors in making this determination. In some examples, if at least onethe described factors for identifying the two minute time period asbeing unclassified is met, the two minute time period is classified asunclassified at block 404. If none of the factors evaluated in blocks401 through 424 are determined to be satisfied according topredetermined criteria, the time period is classified as either AF ornon-AF. As such, the AF score is determined based on the populatedLorenz plot histogram as described above. If the AF score is greaterthan an AF threshold at block 426, the two minute time period isclassified as AF at block 406. On the other hand, if the AF score is notgreater than the AF threshold, “No” branch of block 426, the two minutetime period is classified as a non-AF at block 408.

It is understood that the determination of whether the time period isclassified as unclassified (block 404), classified as AF (block 406), orclassified as non-AF (block 408), may be made in any order, or at thesame time, so that the determination of the two minute time period asbeing an unclassified time period may be used to override an initialdetermination of the two minute time period as being classified as AF ornon-AF, or be made prior to determining the AF score for making aclassification based on the AF score.

FIG. 8 is a schematic diagram of atrial fibrillation detection that maybe performed by a medical device according to one example. The examplesdescribed in FIG. 8 will be described in the context of havingpredetermined time periods that are two minutes in length. However, thetechniques described in FIG. 8 can be for predetermined time periodsthat are longer or shorter than two minutes.

As illustrated in FIG. 8 , the processor 224 classifies the cardiacsignal of each two minute time period as being either AF, non-AF orunclassified using the method described in conjunction with FIG. 7 . Theclassifications of the time periods are used to detect an AF episode.For example, once a predetermined number of two minute time periods,such as three time periods, have been classified as AF, the devicedetects the AF episode. Therefore, as illustrated in the scenario oftiming diagram (a) of FIG. 8 , once the predetermined number of twominute time periods, 500, 502 and 504, are classified as AF, processor224 detects the AF episode at time 505. The processor 224 may track thenumber of two minute time periods classified as AF by updating an AFevent counter each time a time period is classified as AF.

However, in the scenario illustrated in timing diagram (b), twoconsecutive two minute time periods 506 and 508 are classified as beingAF, but the next two minute time period 510 is determined to beunclassified, followed by a subsequent time period 512 being classifiedas AF. According to one example, processor 224 may ignore theunclassified two minute time period 510 and detect an AF episode at time513 once the third time period 512 is classified as AF, so that an AFepisode may be detected despite one or more intermittent unclassifiedtwo minute time periods occurring between AF classifications of timeperiods.

In the timing diagram of scenario (b), at the identification of twominute time period 506, an AF event counter may be incremented to one.At the identification of subsequent two minute period 508, the AF eventcounter is incremented to two. At the identification of subsequent twominute time period 510, since the event was determined to beunclassified, the AF event counter remains at a count of two. At theclassification of subsequent two minute time period 512, the AF eventcounter is incremented to three, and an AF episode is detected inresponse to the AF event counter reaching the AF detection threshold,which is 3 in this example.

As illustrated in the timing diagram of scenario (c), the classificationof one or more time periods 518 and 520 as non-AF result in no detectionof an AF episode. During the determination of whether the predeterminednumber of two minute time periods are classified as AF, the processor224 updates the AF event counter each time an AF classification is madeas described above. For example, upon classification of two minute timeperiod 514, the AF event counter is incremented to one, and at theclassification of subsequent two minute time period 514, the AF eventcounter is incremented to two. If two minute time period 518 were alsoclassified as AF, processor 224 would detect an AF episode, since threetwo minute time periods classified as AF would have occurred, e.g. asdescribed in the timing diagram of scenario (a) above. However, sincetwo minute time period 518 was classified as non-AF, an AF episodedetection is not made. The non-AF classification of time period 518 maybe evidence that an AF episode causing AF classifications of timeperiods 514 and 516 is terminated or a non-sustained AF episode. Inresponse to classifying time period 518 as non-AF, the AF event counteris reset to zero. In other examples, the AF counter may be decreasedwhen a time period is classified as non-AF rather than immediately resetto zero.

In the timing diagram of scenario (d), at the classification of twominute time period 522 as being AF, the AF event counter is incrementedto one, and at the classification of subsequent two minute time period524 as AF, the AF event counter is incremented to two. At theclassifications of subsequent two minute time periods 526 and 528, bothdetermined to be unclassified, the AF event counter remains unchanged ata count of two. Upon classification of subsequent two minute time period530 as being AF, the AF event counter is increased to three, and an AFepisode is detected at time 531.

Had any of time periods 524, 526, 528 or 530 been classified as non-AF,the AF event counter would have been reset to zero, and the processrepeated starting with the next classified two minute interval. However,in addition to resetting the AF event counter in response to a twominute time period being classified as a non-AF time period, processor224 may also be configured to reset the AF event counter to zero if apredetermined number of two minute time periods are determined to beunclassified. For example, five consecutive two minute time periodsdetermined to be unclassified may cause the AF event counter to bereset. In other examples, more than five or fewer than five unclassifiedtime periods, which may not be required to be consecutive, may cause theAF counter to be decremented or reset to zero. Therefore, in the timingdiagram of scenario (e), at the identification of two minute time period532 as AF, the AF event counter is incremented to one. At theidentification of subsequent two minute time period 534 as AF, the AFevent counter is incremented to two. At the identification of the foursubsequent two minute time periods 536, 538, 540 and 542, all determinedto be unclassified, the AF event count remains unchanged at two. In theexample shown, the next two minute time period 546 is classified as AF.The AF event counter is incremented from two to three, and an AF episodeis detected at 545 by processor 224 in response to the AF event counterreaching the threshold count, which is three in this example.

On the other hand, if the subsequent two minute time period 546 isdetermined to be unclassified, the AF event counter would be reset tozero in response to a threshold number (five in this example) ofconsecutive unclassified time period. In the case of time period 546being classified as a non-AF time period, the AF event counter wouldalso be reset to zero. In either of these two cases, if the time periods532 and 534 represent a true AF episode, the AF episode has terminatedor is non-sustained as evidenced by the unclassified and/or non-AFclassified time periods. The process is repeated starting with the nextclassified two minute interval.

FIG. 9 is a schematic diagram of a method for detecting atrialfibrillation that may be performed by ICD 10 (or ICD 10′, ICD 110 orcardiac monitoring device 60) according to another example. The examplesdescribed in FIG. 9 will be described in the context of havingpredetermined time periods that are two minutes in length and an AFdetection threshold set equal to 3 time periods classified as AF.However, the techniques described may utilize different time perioddurations and/or different thresholds. For example, the predeterminedtime period may be between one to five minutes and the number of timeperiods classified as AF may be greater than or equal to one and lessthan or equal to five.

As described above, the processor 224 classifies the cardiac signalwithin each two minute time period as being either AF, non-AF orunclassified using the method described in conjunction with FIG. 7 . Iffactors that cause the two minute time period to be unclassified are notsatisfied, each two-minute time period is classified as AF or non-AFbased on the AF score. In the method of FIG. 9 , the threshold that theAF score is compared to for classifying a time period is not a fixedvalue but is dynamically adjusted by processor 224 in response toclassifications of two-minute time periods.

For example, once a predetermined number of time periods, such as onetime period, has been classified as AF based on a first AF scorethreshold value, if the next predetermined number of time periods areclassified as any combination of AF and/or unclassified, the AF scorethreshold is adjusted to a second, lower value. In other words,following an initial AF classification using the first, higher AF scorethreshold, processor 224 decreases the AF score threshold to the secondlower value at the expiration of a predetermined number of nextconsecutive time periods, e.g., two consecutive time periods followingthe initial AF classification in the examples illustrated in FIG. 9 , aslong as none of the predetermined number of next consecutive timeperiods are classified as non-AF. In other instances, the predeterminednumber of next consecutive time periods may be less than two, e.g., zeroor one, or more than two. If any of the predetermined number of nextconsecutive time periods following an initial AF classification areclassified as non-AF, the AF score threshold remains at the first higherthreshold value.

Therefore, as illustrated in the scenario of timing diagram (a) of FIG.9 , an initial time period 610 is classified as AF based on the AF scoredetermined for time period 610 being greater than a first AF scorethreshold 602 and analysis of other classification factors does not leadto an unclassified time period (as described with FIG. 7 ). The first AFscore threshold 602 stays in effect for at least two more consecutivetime periods 612 and 614 in this example. If both of these time periodsare also classified as AF, in response to an AF score exceeding thefirst AF score threshold 602, AF is detected at time 622. Additionally,processor 224 adjusts the AF score threshold to a second, lower AF scorethreshold 604. The AF score of subsequent time periods will be comparedto this lower threshold 604 for classifying the respective time periods.

The lower AF score threshold 604 may be set to a percentage of theinitial AF score threshold 602, e.g., approximately 75% of the initialAF score. To illustrate, when the maximum possible value of the AF scoreis 100, the first AF score threshold may be set at 75 and adjusted to asecond, lower AF score of 57. In another example, the first AF scorethreshold is 60 and the second is 45. In still other examples, the firstAF score threshold is 60 and the second is 45, the first is 50 and thesecond is 38, the first is 40 and the second is 30, or the first is 25and the second is 19. A user may program the AF score thresholds basedon selection of a least sensitive, e.g. first threshold of 75 and secondthreshold of 57, to most sensitive, e.g., first threshold 25 and secondthreshold 19, with the other example given above corresponding to a lesssensitive setting (first threshold 60 and second threshold 45), balancedsensitivity (first threshold 50 and second threshold 38), and moresensitivity (first threshold 40 and second threshold 30). In otherexamples, the actual values of the first and second thresholds may beprogrammable selected individually in any combination of a first range,e.g., from 25 to and including 75 for the first threshold, and a secondrange, e.g., from 19 to and including 57 for the second threshold, aslong as the first threshold is greater than the second threshold value.In other examples, the second threshold may be set to be anotherpercentage of the initial threshold, e.g., between 65-85%, 70-80%, orsome other percentage.

By reducing the AF score for subsequent time periods, AF detectionsensitivity is increased at appropriate times while AF detectionspecificity is maintained by using the first higher AF score thresholdand applying the factors that lead to unclassified time periods. Forexample, the next two consecutive time periods 616 and 618 are bothclassified as AF based on an AF score exceeding the second threshold604, even though the first, higher threshold 602 is not met (and factorsleading to an unclassified classification are not present). The detectedAF episode is detected as still being in progress during time periods616 and 618 even though the AF scores for these time periods 616 and 618are each less than the first threshold 602. The next time period 620 isclassified as non-AF due to an AF score being less than the secondthreshold 604. In response to the non-AF classification, processor 224adjusts the AF score threshold from the lower threshold 604 back to thehigher threshold 602 at time 624. Termination of the AF episode isdetected in response to the non-AF classification. The AF episodeduration 615 is the time interval from the start of the earliest timeperiod 610 classified as AF that led to AF detection at time 622 to theend of last AF classification time period 618 that precedes terminationdetection at time 624, i.e., that precedes the time period 620classified as non-AF.

In the scenario illustrated in timing diagram (b), two consecutive twominute time periods 632 and 634 are classified as being unclassifiedafter an initial time period 630 is classified as AF based on the firstAF score threshold 602. In response to no non-AF classifications of thetwo time periods 632 and 634 following the initial AF classification oftime period 630, processor 224 adjusts the AF score threshold at time642 to the second lower threshold 604. Three consecutive classificationsincluding at least an initial AF classification and no non-AFclassifications cause an adjustment of the AF score threshold. As such,in one example, time periods 632 and 634 immediately and consecutivelyfollowing the initial AF classified time period 630 may both beunclassified (as shown in this example), both be classified as AF, orone classified as AF and one unclassified to cause the AF scorethreshold to be adjusted at time 642.

Since only one time period 630 has been classified as AF in the exampleshown, however, an AF detection is not made at time 642 when the AFscore threshold is adjusted. The next two time periods 636 and 638 areclassified as AF in response to an AF score being greater than theadjusted AF score threshold 604 (and factors that would cause anunclassified classification to be made not being determined). When theAF event counter reaches a count of three at time 643, an AF detectionis made. The next time period 640 is classified as non-AF in thisexample. Termination of the AF episode is detected, and the AF scorethreshold is adjusted from the lower value 604 back up to the highervalue 602 at time 644 in response to the non-AF classification andresulting episode termination detection.

The episode duration 635 starts with the earliest time period 630 thatwas classified as AF and led to AF detection at time 643 and extendsthrough the latest AF-classified time period 638 prior to terminationdetection at time 644. The episode duration 635 includes unclassifiedtime periods 632 and 634 that do not lead to detection of termination attime 644. Unclassified time periods 632 and 634 occur betweenAF-classified time periods 630 and 636 and are therefore included in AFepisode duration 635. The time periods 632 and 634 may be classified asunclassified due to any of the other factors described in FIG. 7 . Inone particular example, one or both of the time periods 632 and 634 maybe classified as unclassified due to ventricular tachyarrhythmiadetection (block 421 of FIG. 7 ). By allowing time periods 632 and 634to be classified as unclassified when ventricular tachyarrhythmia isbeing detected, the detection of AF and determination of the AF episodeduration 635 are uninterrupted. The detection of an AF episode that isconcurrent with a ventricular tachyarrhythmia episode provides importantdiagnostic information for the clinician to use in properly determiningthe patient's heart rhythm status and subsequent treatment.

In scenario (b) and other scenarios that follow, the time periodsdetermined to be unclassified, e.g., time periods 632 and 634 arerepresented as having AF scores being equal to the currently set AFscore threshold. It is to be understood, however, that an actual AFscore, if determined, may be greater than, equal to, or less than thecurrent value of the AF score threshold but is not used to classify thetime period when the analysis of other factors cause the time period tobe determined as unclassified as described in conjunction with FIG. 7 .In some cases, if the time period is determined to be unclassified dueto analysis of one or more factors as described in conjunction with FIG.7 , determination of an AF score for the current time period may not bemade; classification of the time period as unclassified may preclude theneed to determine the AF score in some examples.

In scenario (c), the AF score threshold is adjusted from a firstthreshold 602 to a second threshold 604 at time 674 after an initial AFclassified time period 650 based on the first, higher threshold 602followed by two consecutive time periods 652 and 654 that do not includea non-AF classification. Processor 224 may increment an AF event counterin response to each AF classification and increment an unclassifiedevent counter in response to each unclassified time period. Accordingly,in the example of scenario (c), at time 674 the AF event counter is at acount of one, and the unclassified event counter is at a count of two.After time period 656, the unclassified event counter is at a count ofthree, and after time period 658 the unclassified event counter is at acount of four. The next two time periods 670 and 672 are classified asAF based on the respective AF scores exceeding the second, lower AFscore threshold 604. In some examples if the next time period 670 isalso an unclassified time period, such that five unclassified timeperiods occur consecutively, the AF event counter and the unclassifiedevent counter may be reset to zero, and the AF score threshold may beincreased to the first, higher AF score threshold 602. Processor 224 maytherefore adjust the AF score threshold and reset counters in responseto detecting a predetermined number of consecutive unclassified timeperiods.

In the example shown, the next time period 670 is classified as AF sothe unclassified event counter remains at a count of four. The AF eventcounter is increased to two after time period 670 and to three aftertime period 672. AF is detected at time 676 in response to the AF eventcount reaching the detection threshold, which is three in this example.The AF score threshold remains at the second, lower threshold 604 untiltermination of the AF episode is detected in response to a non-AFclassification, e.g., time period 675, or a predetermined number ofconsecutive unclassified time periods, e.g., five consecutiveunclassified time periods. At time 678, the AF score threshold isadjusted to the first, higher threshold 602 in response to the non-AFclassification of time period 675. As shown by the example of scenarios(b) and (c), an AF episode may be detected after the AF threshold isadjusted to the second, lower threshold.

The episode duration 655 in scenario (c) begins with AF time period 650and extends through AF time period 672 which led to AF detection at time676. This episode duration 655 includes the consecutive unclassifiedtime periods 652, 654, 656, and 658 which do not lead to detection of AFtermination at 678.

Scenario (d) shows another example of a series of two-minute time periodclassifications and the corresponding adjustment to the AF scorethreshold. An initial time period 680 is classified as AF based on thefirst, higher AF score threshold 602. The AF event counter is increasedto a count of one. The next time period 682 is classified as non-AFbased on the first AF score threshold 604. The AF event counter may bereset to zero in response to the non-AF classification. The unclassifiedtime period 684 may not be counted by processor 224 since the AF eventcounter is currently zero.

A subsequent sequence of AF-U-AF (time periods 686, 688 and 690,respectively) result in an AF event count of two and an unclassifiedevent count of one. The two consecutive time periods 688 and 690following the AF time period 686 which are classified as unclassifiedand AF, respectively, result in a combined event count of the AF andunclassified time periods being equal to three. In response to thiscombined event count of three, processor 224 adjusts the AF scorethreshold from the first, higher AF score threshold 602 to the secondlower AF score threshold 604 at time 695. AF is not yet detected becausethe AF event count is two. The next time period 692 is classified as AFbased on a comparison of the AF score to the second, lower AF scorethreshold 604. Processor 224 increases the AF event count to three anddetects AF at time 697 in response to the AF event count reaching thedetection threshold. Upon detecting AF at time 697, the unclassifiedevent counter is reset to zero. The unclassified event counter willcount unclassified time segments beginning from zero after the AFdetection in order to count consecutive unclassified time periods fordetecting termination of the AF episode. The unclassified event countreaches two after time periods 694 and 696. The next time period 698 isclassified as non-AF resulting in detecting termination of the AFepisode at time 699. All event counters are reset to zero, and the AFscore threshold is adjusted back to the first, higher threshold 602 attime 699.

The episode duration 685 starts with AF-classified time period 686 whichis the earliest AF classified episode that led to AF detection at time697. The episode duration includes unclassified time period 688 whichdid not contribute to detection of termination at block 699. Episodeduration 685 ends with the last AF-classified time period 692 prior todetecting termination at time 699. Unclassified time periods 694 and 696may, in some instances, not be included in the episode duration 685because they immediately precede the non-AF classified time period 698that results in episode termination detection with no interveningAF-classified episode. In other instances, however, those unclassifiedtime periods may also be included in the episode duration 655.

The first and second AF score thresholds may be fixed values or may beprogrammable by a user. In one example, a user may program the first andsecond AF score thresholds to be increased or set to a relatively highervalue than currently programmed or decreased or set to a relativelylower value than currently programmed. Both the first and second AFscore thresholds are adjusted together up or down by the same incrementor decrement respectively, in response to the user-entered programmingcommand. In other examples, a user may programmably select each of thefirst and second AF score thresholds tailored to individual patientneed.

While only two different AF score thresholds 602 and 604 are illustratedin the example of FIG. 9 , it is understood that the AF score thresholdmay be adjusted between three or more AF score threshold values in otherexamples. For instance, after AF detection is made at time 697, the AFscore threshold set to the second, lower threshold 604 could be reducedto a third lowest AF score threshold to allow continuing detection ofthe AF episode using less stringent criteria than the initial AFdetection criteria. In other examples, once the AF detection is made attime 697, the AF score threshold could be increased from the second,lower threshold 604 back up to the first, higher threshold 602 or to athird, intermediate threshold value between the second, lower threshold604 and the first, higher threshold 602. The third intermediatethreshold value may be applied for classifying subsequent time periodsuntil termination of the AF episode is detected based on a predeterminednumber of time periods being classified as non-AF based on an AF scorefalling below the third intermediate threshold value.

In the example scenarios of FIG. 9 , the AF score threshold is adjustedafter at least two consecutive time period classifications of anycombination of AF and unclassified immediately follow a preceding orinitial AF classified time period. In the example of two minute timeintervals, the AF score threshold is adjusted after six minutes with nonon-AF classification. In other examples, the AF score threshold may beadjusted after fewer or more time periods. For example, a single timeperiod classified as AF may cause the AF score threshold to be reducedto a second lower value. In other words, the AF score threshold may beadjusted immediately in response to time period 610, 630, 650, or 680being classified as AF, e.g., immediately after the first AF classifiedtime period. In other examples, at least one unclassified or AF timeperiod following an immediately preceding AF time period may cause theAF score threshold to be adjusted. In still other examples, more thantwo time periods that are not classified a non-AF and consecutivelyfollow a first time period classified as AF may be required beforeadjusting the AF score threshold. Thus, total duration from thebeginning of the first time period classified as AF until the AF scorethreshold is adjusted may be greater than or equal to two minutes andless than or equal to ten minutes, for example.

FIG. 10 is a flowchart 700 of a method for detecting atrialfibrillation, according to one example. At block 702, the classificationof the current time period is determined. If the classification is AF,as determined at block 704, processor 224 increases the AF event counterat block 706 and advances to block 714 to compare a combined count ofthe AF event counter and the unclassified event counter to a threshold.If the combined counts do not meet the threshold at block 714, the AFevent count is compared to the AF detection threshold at block 718.

If the time period is not classified as AF, “No” branch of block 704,and is classified as non-AF, “Yes” branch of block 708, the processor224 advances to block 742. The AF classification criteria, if previouslyadjusted, are restored to initial values. For example, if an AF scorethreshold has been previously adjusted to a second lower threshold, theAF score threshold is returned to a higher first threshold as describedin conjunction with FIG. 9 . At block 746, the AF event counter and theunclassified event counter are reset to zero if they have beenpreviously incremented to a non-zero value.

If the current time period classification obtained at block 702 isneither AF nor non-AF, i.e., if the current time period is determined tobe unclassified, “No” branch of block 708, and the AF counter iscurrently inactive with a value of zero, “No” branch of block 710,processor 224 determines the classification of the next time period atblock 702. If the AF event count is greater than zero as determined atblock 710, indicating that an initial AF classification has been made,and the current time period is unclassified, processor 224 increases theunclassified event count by one at block 712. The unclassified eventcount may be used for controlling adjustment of AF classificationcriteria prior to an AF detection being made as described in conjunctionwith FIG. 9 . If the unclassified event count has reached apredetermined threshold, “Yes” branch of block 713, processor mayrestore initial AF classification criteria (if previously adjusted) atblock 742 and reset the unclassified event counter and the AF eventcounter to zero at block 746. The process begins again at block 702 withthe classification of the next time period.

After increasing the AF event count at block 706 or increasing theunclassified event count at block 712, if the unclassified event counthas not reached the predetermined threshold, “No” of block 713, thecombined event count may be compared to a threshold at block 714. Whenthe combined count of the AF event counter and the unclassified eventcounter has reached a threshold at block 714, e.g., a combined count ofthree, the AF classification criteria may be adjusted at block 716. Inone example, processor 224 adjusts the AF classification criteria bydecreasing the AF score threshold to a second lower threshold afterclassifying a first time period as AF and classifying the next twoconsecutive time periods as any combination of AF or unclassified basedon the first higher AF score threshold as described above. The AFclassification criteria may therefore be adjusted in response to threeconsecutive time periods being classified as AF, a sequence of AF-U-AFor a sequence of AF-U-U.

It is to be understood that in some examples once the combined countreaches a predetermined threshold at block 714, and the AFclassification criteria have been adjusted at block 716 prior to an AFdetection being made, the AF classification criteria are not adjustedagain until AF episode termination is detected, e.g., based on a timeperiod classified as being non-AF (block 708) or based on apredetermined number of unclassified time periods (block 713), e.g.,five consecutive unclassified time periods. In other examples,additional adjustments to the AF score may be made before AF episodetermination is detected, e.g., to a third AF score threshold or back tothe first, highest AF score threshold, as described above.

At block 718, processor 224 compares the AF event count to the AFdetection threshold. When the AF detection threshold has not beenreached, processor 224 returns to block 702 to obtain the next timeperiod classification. As described above, after adjusting the AFclassification criteria at block 716, if a non-AF classification is made(“Yes” branch of block 708) before detecting AF, the AF classificationcriteria are restored to the initial classification criteria at block742 and all AF event and unclassified event counters are reset to zeroat block 746. If subsequent time periods are classified as AF, “Yes”branch of block 704, the AF event count is increased accordingly atblock 706.

If the AF event count reaches a detection threshold, “Yes” branch ofblock 718, processor 224 detects AF at block 720. An AF detectionresponse is provided at block 721. The response to AF detection mayinclude controlling pace timing and control 212 to deliver an atrialanti-arrhythmia therapy or withhold a ventricular therapy. The responseto AF detection may additionally or alternatively include storing datarelating to the AF episode, such as the time of onset, the totalduration (as determined from the AV event counter upon detection oftermination of the AF episode as discussed below or computed using thetechniques described in FIG. 9 ), storing an episode of the cardiacelectrical signal in RAM 226 and/or other data relating to the AF event.The data may be transmitted to external device 40 (FIG. 1 ) fordisplaying or communicating the data to a clinician for use in managingthe patient.

When an AF detection is made at block 720, the unclassified eventcounter is reset to a count of zero at block 722. Processor 224 maybegin counting subsequent time periods determined to be unclassifiedafter AF detection is made for detecting termination of the AF episode.The next time period classification is obtained at block 724. If thenext time period classification is AF, as determined at block 726, theAF event count is increased at block 728. AF classifications made afterAF detection are based on the adjusted AF classification criteria. TheAF event counter may continue to be increased with each AFclassification made after detecting AF at block 720 for use indetermining the duration of the AF episode and determining AF burden(e.g., the combined duration of all detected AF episodes over a givenmonitoring interval such as 24 hours). Such AF episode data may betransmitted to an external medical device for display or communicationto a clinician thereby providing useful information to the clinician inmaking diagnostic and therapy management decisions.

If the classification of the next time period is not AF, “No” branch ofblock 726, but is non-AF, “Yes” branch of block 730, termination of theAF episode is detected at block 740. If the classification of the nexttime period is neither AF nor non-AF, “No” branch of block 730, i.e., ifthe time period is determined to be unclassified as indicated at block732, the unclassified event counter is increased by one at block 734.The unclassified event counter is compared to a threshold at block 736.If the threshold is not reached, processor 224 returns to block 724 tofetch the next time period classification. If the unclassified countreaches a threshold at block 736, e.g., five consecutive unclassifiedtime periods, termination of the AF episode is detected at block 740.

If episode termination is detected, the initial AF classificationcriteria are restored at block 742, and the AF event and unclassifiedevent counters are reset at block 746. The process begins again at block702.

FIG. 11 is a flow chart 800 of a method performed by ICD 10 or ICD 110for providing a response to detecting AF according to one example. If anAF detection is made at block 802, e.g., as described in conjunctionwith any of FIGS. 8-10 , an AF episode record is stored at block 804.The AF episode record may include a Lorenz plot or histogram of RRI datathat led to AF classifications and AF detection. The episode recordstored at block 804 may further include the start time, terminationtime, and total duration of the AF episode. Referring again to FIG. 9 ,examples of episode durations 615, 635, 655, and 685 are shown extendingfrom the start of the first respective AF classified time period thatled to AF detection and ending with the last AF classified time periodthat leads to detection of termination of the AF episode. Unclassifiedepisodes that lead to termination detection, e.g., unclassified episodes694 and 696 in scenario (d) may not be included in the episode duration,whereas unclassified episodes that do not immediately precedetermination detection, e.g., unclassified episodes 652, 654, 656 and 658in scenario (c), are included in the episode duration, e.g., duration655.

When unclassified time periods are included in the AF episode or lead totermination detection of the AF episode, the factor(s) leading todetermining the time period as being unclassified may be stored with theAF episode record. For example, if the time period is determined to beunclassified due to other episodes being detected such as VT or VF, dueto oversensing, due to too many short RRIs, or due to too manyventricular pacing pulses during the time period, this factor may bestored to provide the clinician with useful information in diagnosingthe patient's heart rhythm status for guiding therapy decisions fortreating the patient's AF.

At block 806, processor 224 may determine AF burden of the patient bycomputed the total time AF was identified over a 24-hour time interval(or other predetermined monitoring interval). Computation of the AFburden may include counting or summing all time periods classified as AFor counting or summing only AF classified time periods that wereincluded in a detected AF episode. AF burden may also include allunclassified time periods that occur during a detected AF episode. Insome examples, unclassified time periods that lead to detectingtermination of the AF episode that are not included in the AF episodeduration are not included in the AF burden computation. For example,referring to FIG. 9 , scenario (d), unclassified time period 684 is notincluded in AF burden computation because it occurs before the AFepisode indicated by episode duration 685. Unclassified time period 688is included in AF burden determination because it occurs during the AFepisode. Unclassified time periods 694 and 696 are not included indetermining AF burden because they lead to termination detection at time699 and are not included in the episode duration 685.

When AF is detected, processor 224 may store a cardiac signal segmentthat is acquired during the detected AF episode. The cardiac signalsegment is stored in memory at block 808 with the normal gain of senseamplifiers 200 and A/D converter 222 used during cardiac signal analysisand processing performed to identify RRIs, analyze the signal foroversensing, etc. For example, the cardiac signal stored at block 808may be an EGM signal acquired using RV coil electrode 28 and ICD housing15 in FIG. 1 . In system 100 of FIG. 3A, the cardiac signal stored atblock 808 may be an ECG signal acquired using defibrillation electrode24 or defibrillation electrode 126 and housing 115. The signal stored atnormal range (e.g., with 8-bit resolution sampled at 128 Hz with A/Dconverter input range of ±12 mV) may be used to provide an unclipped EGMor ECG signal for morphology analysis (e.g., wavelet template matching)and for storing unclipped cardiac signal episodes in response todetecting a tachyarrhythmia. The normal range signal stored at block 808may be selected as a far-field or relatively global cardiac electricalsignal that is used to produce a display of the electrical rhythm of thepatient's heart clearly showing R-wave morphology and regularity of RRIsfor the clinician to see a high level view of the signal and thepatient's corresponding rhythm. However, depending on the sensingvector, the normal range cardiac signal stored at block 808 may notinclude observable or easily observed P-waves.

As such, when AF is detected, the processor 224 stores a second cardiacsignal in memory at block 810 with a lower range, higher gain setting,e.g., a range of ±2 mV which may be controlled by adjusting the A/Dconverter input range. The high gain, lower range setting provides aclearer view of P-waves in the stored cardiac signal segment whendisplayed by external device 40. The high gain, lower range setting mayresult in clipping of R-waves in the stored second cardiac signal.However, the first cardiac signal stored at normal range provides areliable, unclipped display of the R-wave morphology.

The second cardiac signal stored with a high gain, lower range settingmay be selected as a second far-field or relatively global signal. Forexample, in system 1 of FIG. 1A or 1B, the second cardiac signal may beacquired between the RV coil electrode 24 and the SVC coil electrode 26,or the SVC coil electrode 26 to the ICD housing 15. In the system 100 ofFIG. 3A, the second cardiac signal may be acquired using the sensingelectrode 128 and sensing electrode 131, one of sensing electrodes 128,130 or 131 paired with one of defibrillation electrodes 124 or 126, orone of electrodes 124, 126, 128, 130 or 131 paired with housing 115.

When ICD 10 or ICD 110 receives an interrogation command from anexternal device 40, processor 224 controls telemetry circuit 330 totransmit the AF episode record, AF burden information, and the storedfirst, normal gain cardiac signal and the second higher gain cardiacsignal. The external device is configured to generate a display of theAF data for the patient to provide the clinician with valuablediagnostic information to support therapy decision-making process.

If AF is not being detected, “No” branch of block 802, processor 224 maybe detecting VT or VF at block 820. If not detecting VT or VF, “No”branch of block 820, processor 224 continues monitoring for cardiactachyarrhythmias at blocks 802 and 820. If AF is not being detected atblock 802 but processor 224 is detecting VT or VF, “Yes” branch of block820, the VT or VF episode record is stored at block 822, which mayinclude rate, duration, start time, end time, delivered therapies andresults, etc. At block 824, a segment of the first cardiac signal withnormal gain acquired during the detected episode is stored. The firstcardiac signal at normal gain may be a far-field or relatively globalsignal as described above that provides a high level view of R-wavemorphology and RRIs and may be the same signal with the same gain thatis stored at block 808 in response to AF detection. At block 826, athird cardiac electrical signal is stored with normal gain.

The third cardiac electrical signal may be a near-field or relativelylocal signal acquired with a different sensing vector than either of thefirst or second cardiac electrical signals stored at blocks 808 and 810.For example, the third cardiac signal stored at block 826 may be an EGMsignal acquired using RV tip electrode 28 and RV ring electrode 30 inFIGS. 1A and 1B. In system 100 of FIG. 3A, the cardiac signal stored atblock 826 may be an ECG signal acquired using sensing electrodes 128 and130. The third cardiac electrical signal is stored with normal gain butis acquired using a near-field or localized ventricular sensing vectorthat can be used to generate a display of a high quality ventricularsignal when VT or VF is detected and no atrial tachyarrhythmia isdetected.

In this way, ICD 10, 10′ or ICD 110 provides a unique response forstoring data depending on whether an atrial tachyarrhythmia is beingdetected, with or without concurrent SVT, VT or VF, or a ventriculartachyarrhythmia is being detected without concurrent AF detection.Storage of a high gain cardiac electrical signal and transmission to anexternal device 40 at block 812 for display to a clinician provides theclinician with valuable diagnostic information relating to the detectedAF episode. When the AF episode is being detected simultaneously with aventricular tachyarrhythmia detection, the relationship between eventsleading to the two detections can be ascertained. However, when only aventricular tachyarrhythmia is detected, storage and transmission of anear-field or localized ventricular signal may provide the clinicianwith important information regarding the ventricular rhythm.

In some examples, processor 224 responds to an AF detection by selectingwhich cardiac electrical signals are stored as described above andtransmits the signals with normal gain and range to external device 40.Processor 52 of external device 40 may automatically generate a displayon user display 54 that includes the first, high gain, low range signalfor observation of P-waves and the second, normal gain, normal rangesignal for unclipped observation of R-waves.

Thus, an apparatus and methods have been presented in the foregoingdescription for detecting and responding to atrial tachyarrhythmia withreference to specific examples. It is appreciated that variousmodifications to the referenced examples may be made, includingmodifying the order of steps performed and/or modifying the combinationsof operations shown in the flow charts presented herein, withoutdeparting from the scope of the following claims.

The invention claimed is:
 1. A medical device, comprising: sensingcircuitry configured to receive a cardiac signal; and a processorconfigured to detect an atrial tachyarrhythmia episode based on thecardiac signal by: identifying R-waves attendant to ventriculardepolarizations in the cardiac signal; determining RR-intervals betweensuccessive R-waves identified in the sensed cardiac signal over each ofa plurality of time periods; determining a variability metric of theRR-intervals for each of the plurality of time periods; determining thata first variability metric determined for a first time period of theplurality of time periods is greater than a first threshold; adjustingthe first threshold to a second threshold lower than the first thresholdin response to at least the first variability metric being greater thanthe first threshold; determining that a second variability metricdetermined for a second time period that is later than the first timeperiod is greater than the second threshold; and detecting the atrialtachyarrhythmia episode in response to at least the first variabilitymetric being greater than the first threshold and the second variabilitymetric being greater than the second threshold.
 2. The medical device ofclaim 1, wherein the processor is configured to: adjust the firstthreshold to the second threshold after a predetermined number ofintervening time periods of the plurality of time periods that occurbetween the first time period and the second time period.
 3. The medicaldevice of claim 2, wherein the processor is further configured to:determine that the variability metric determined for at least one of thepredetermined number of intervening time periods is greater than thefirst threshold; and adjust the first threshold to the second thresholdafter the predetermined number of intervening time periods in responseto the first variability metric being greater than the first thresholdand the variability metric determined for at least one of thepredetermined number of intervening time periods being greater than thefirst threshold.
 4. The medical device of claim 2, wherein the processoris further configured to: determine classification factors from theR-waves identified over each of the predetermined number of interveningtime periods; determine at least one of the predetermined number ofintervening time periods as being unclassified based on comparing thedetermined classification factors to classification criteria; and adjustthe first threshold to the second threshold after the predeterminednumber of intervening time periods in response to the first variabilitymetric being greater than the first threshold and at least one of thepredetermined number of intervening time periods being unclassified. 5.The medical device of claim 1, wherein the processor is furtherconfigured to: determine that the variability metric determined for atleast a threshold number of the plurality of time periods is greaterthan at least one of the first threshold and the second threshold; anddetect the atrial tachyarrhythmia episode in response to the variabilitymetric determined for at least the threshold number of the plurality oftime periods being greater than at least one of the first threshold andthe second threshold.
 6. The medical device of claim 5, wherein theprocessor is further configured to determine an episode duration of thedetected atrial tachyarrhythmia episode, the episode duration comprisingthe threshold number of the plurality of time periods each having thevariability metric greater than at least one of the first threshold andthe second threshold.
 7. The medical device of claim 1, wherein theprocessor is further configured to: after detecting the atrialtachyarrhythmia episode, determine that the variability metric for atleast one time period of the plurality of time periods is less than thesecond threshold; and detect termination of the atrial tachyarrhythmiaepisode in response to the variability metric for the at least one timeperiod of the plurality of time periods being less than the secondthreshold.
 8. The medical device of claim 7, wherein the processor isfurther configured to: determine classification factors from the R-wavesidentified over each of the plurality of time periods; determine atleast one of the plurality of time periods that occur after the firsttime period and prior to detecting termination of the atrialtachyarrhythmia episode as being unclassified based on comparing thedetermined classification factors to classification criteria; anddetermine an episode duration of the detected atrial tachyarrhythmiaepisode, the episode duration comprising the at least one of theplurality of time periods determined as being unclassified.
 9. Themedical device of claim 7, wherein the processor is further configuredto adjust the second threshold back to the first threshold in responseto detecting termination of the atrial tachyarrhythmia episode.
 10. Themedical device of claim 7, wherein the processor is further configuredto: determine a total time period of the plurality of time periods thatoccur during the detected atrial arrhythmia episode that each have thevariability metric greater than one of the first threshold and thesecond threshold; and determining an atrial tachyarrhythmia burden basedon at least the total time period.
 11. A method, comprising: receiving acardiac signal; identifying R-waves in the cardiac signal; determiningRR-intervals between successive R-waves identified in the sensed cardiacsignal over each of a plurality of time periods; determining avariability metric of the RR-intervals for each of the plurality of timeperiods; determining that a first variability metric determined for afirst time period of the plurality of time periods is greater than afirst threshold; adjusting the first threshold to a second thresholdless than the first threshold in response to at least the firstvariability metric being greater than the first threshold; determiningthat a second variability metric determined for a second time periodthat is later than the first time period is greater than the secondthreshold; and detecting an atrial tachyarrhythmia episode in responseto at least the first variability metric being greater than the firstthreshold and the second variability metric being greater than thesecond threshold.
 12. The method of claim 11, comprising: adjusting thefirst threshold to the second threshold after a predetermined number ofintervening time periods of the plurality of time periods that occurbetween the first time period and the second time period.
 13. The methodof claim 12, further comprising: determining that the variability metricdetermined for at least one of the predetermined number of interveningtime periods is greater than the first threshold; and adjust the firstthreshold to the second threshold after the predetermined number ofintervening time periods in response to the first variability metricbeing greater than the first threshold and the variability metricdetermined for at least one of the predetermined number of interveningtime periods being greater than the first threshold.
 14. The method ofclaim 12, further comprising: determining classification factors fromthe R-waves identified over each of the predetermined number ofintervening time periods; determining at least one of the predeterminednumber of intervening time periods as being unclassified based oncomparing the determined classification factors to classificationcriteria; and adjusting the first threshold to the second thresholdafter the predetermined number of intervening time periods in responseto the first variability metric being greater than the first thresholdand at least one of the predetermined number of intervening time periodsbeing unclassified.
 15. The method of claim 11, further comprising:determining that the variability metric determined for at least athreshold number of the plurality of time periods is greater than atleast one of the first threshold and the second threshold; and detectingthe atrial tachyarrhythmia episode in response to the variability metricdetermined for at least the threshold number of the plurality of timeperiods being greater than at least one of the first threshold and thesecond threshold.
 16. The method of claim 15, further comprisingdetermining an episode duration of the detected atrial tachyarrhythmiaepisode, the episode duration comprising the threshold number of theplurality of time periods each having the variability metric greaterthan at least one of the first threshold and the second threshold. 17.The method of claim 11, further comprising: after detecting the atrialtachyarrhythmia episode, determining that the variability metric for atleast one time period of the plurality of time periods is less than thesecond threshold; and detecting termination of the atrialtachyarrhythmia episode in response to the variability metric for the atleast one time period of the plurality of time periods being less thanthe second threshold.
 18. The method of claim 17, further comprising:determining classification factors from the R-waves identified over eachof the plurality of time periods; determining at least one of theplurality of time periods that occur after the first time period andprior to detecting termination of the atrial tachyarrhythmia episode asbeing unclassified based on comparing the determined classificationfactors to classification criteria; and determining an episode durationof the detected atrial tachyarrhythmia episode, the episode durationcomprising the at least one of the plurality of time periods determinedas being unclassified.
 19. The method of claim 17, further comprisingadjusting the second threshold back to the first threshold in responseto detecting termination of the atrial tachyarrhythmia episode.
 20. Themethod of claim 17, further comprising: determining a total time periodof the plurality of time periods during the detected atrial arrhythmiaepisode that each have the variability metric greater than one of thefirst threshold and the second threshold; and determining an atrialtachyarrhythmia burden based on at least the total time period.
 21. Anon-transitory computer-readable medium storing instructions, which whenexecuted by a processor of a medical device cause the device to: receivea cardiac electrical signal; identify R-waves in the cardiac signal;determine RR-intervals between successive R-waves identified in thesensed cardiac signal over each of a plurality of time periods;determine a variability metric of the RR-intervals for each of theplurality of time periods; determine that a first variability metricdetermined for a first time period of the plurality of time periods isgreater than a first threshold; adjust the first threshold to a secondthreshold less than the first threshold in response to at least thefirst variability metric being greater than the first threshold;determine that a second variability metric determined for a second timeperiod that is later than the first time period is greater than thesecond threshold; and detect an atrial tachyarrhythmia episode inresponse to at least the first variability metric being greater than thefirst threshold and the second variability metric being greater than thesecond threshold.